Sustainable Development in Practice: Sustainomics Methodology and Applications (Munasinghe Institute for Development (Mind) Series on Growth and Sustainable Development)

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SUSTAINABLE DEVELOPMENT IN PRACTICE Sustainomics Methodology and Applications

This book provides a comprehensive, rigorous and practical analysis of sustainable development prospects today by applying the innovative sustainomics framework. Developed over the past 18 years by the eminent environmental scientist and development expert, Mohan Munasinghe, sustainomics shows us the first practical steps in making the transition from the risky business-as-usual scenario to a safe and sustainable future. Its main message is optimistic: although the problems are serious, an effective response can be mounted to make development more sustainable if it is initiated immediately. The book explains the key principles underlying sustainomics cogently, concisely and with a minimum of technical jargon, with mathematical and other details being provided in annexes. It illustrates the methodology with empirical case studies that are practical and policy-relevant over a wide range of time and geographic scales, countries, sectors, ecosystems and circumstances. The extensive bibliography is useful to researchers of specific issues within sustainable development. This book appeals to a wide audience, including students, researchers from many disciplines, policy analysts, public and private decision makers, and development practitioners. p r o f e s s o r m o h a n m u n a s i n g h e is co-winner of the 2007 Nobel Prize for Peace, as Vice Chair of the UN Intergovernmental Panel on Climate Change (IPCC-AR4). He is the Chairman of the Munasinghe Institute of Development (MIND), Sri Lanka, Director General of the Sustainable Consumption Institute (SCI), University of Manchester, UK, and Honorary Senior Advisor to the Sri Lankan Government. During 35 years of distinguished public service, he has served as Senior Energy Advisor to the President of Sri Lanka, Advisor to the United States Presidents Council on Environmental Quality, and Senior Advisor/Director at the World Bank. p r o f e s s o r m u n a s i n g h e has earned graduate degrees in engineering, physics and development economics from Cambridge University (UK), Massachusetts Institute of Technology (USA), and McGill University and Concordia University (Canada). He has also received several honorary doctorates (honoris causa). He is a Fellow of several internationally recognized Academies of Science and serves on the editorial board of 12 academic journals. He has authored 92 books and over 300 technical papers on economics, sustainable development, climate change, power, energy, water resources, transport, environment, disasters, and information technology.

munasinghe institute for development (mind) series on growth and sustainable development Series Editor Mohan Munasinghe Chairman, Munasinghe Institute for Development, Sri Lanka Vice Chair, Intergovernmental Panel on Climate Change (IPCC), Switzerland Honorary Advisor to the Government, Sri Lanka Visiting Professor, United Nations University, Japan This series of volumes deals with the interaction between conventional economic growth and the more recent paradigm of sustainable development. A distinguished group of international experts drawn from a broad range of disciplines examine this nexus, and suggest ways for making development more sustainable in the future. The volumes cover both theory and practical applications at global, national and local levels: 1. The Sustainability of Long-term Growth: Socioeconomic and Ecological Perspectives, Mohan Munasinghe, Osvaldo Sunkel and Carlos de Miguel (Cheltenham: Edward Elgar, 2001). 2. Sustainable Energy in Developing Countries: Policy Analysis and Case Studies, Peter Meier and Mohan Munasinghe (Cheltenham: Edward Elgar, 2005). 3. Primer on Climate Change and Sustainable Development: Facts, Policy Analysis and Applications, Mohan Munasinghe and Rob Swart (Cambridge: Cambridge University Press, 2005). 4. Macroeconomic Policies for Sustainable Growth: Analytical Framework and Policy Studies of Brazil and Chile, Mohan Munasinghe, Raul O’Ryan, Ronaldo Seroa da Motta, Carlos de Miguel, Carlos Young, Sebastian Miller and Claudio Ferraz (Cheltenham: Edward Elgar, 2006). 5. Global Agenda for Sustainable Governance of Ecosystems: Lessons from the Millennium Ecosystems Assessment, Janet Ranganathan, Mohan Munasinghe and Frances Irwin (Cheltenham: Edward Elgar, 2007).

SUSTAINABLE DEVELOPMENT IN PRACTICE Sustainomics Methodology and Applications Mohan Munasinghe Munasinghe Institute for Development (MIND), Sri Lanka

Foreword by James Gustave Speth Munasinghe Institute for Development (MIND) Colombo, Sri Lanka • Montreal, Canada • Gaithersberg MD, USA

Environment

Munasinghe Institute for Development ‘making development more sustainable-MDMS’

MIND Society

Economy

CAMBRIDGE UNIVERSITY PRESS

Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, São Paulo Cambridge University Press The Edinburgh Building, Cambridge CB2 8RU, UK Published in the United States of America by Cambridge University Press, New York www.cambridge.org Information on this title: www.cambridge.org/9780521895408 © M. Munasinghe 2009 This publication is in copyright. Subject to statutory exception and to the provision of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. First published in print format 2009

ISBN-13

978-0-511-53996-1

eBook (EBL)

ISBN-13

978-0-521-89540-8

hardback

ISBN-13

978-0-521-71972-8

paperback

Cambridge University Press has no responsibility for the persistence or accuracy of urls for external or third-party internet websites referred to in this publication, and does not guarantee that any content on such websites is, or will remain, accurate or appropriate.

To my granddaughter Linara (Lena) and her progeny – in the fond hope that they will inherit a world that is more sustainable than ours

Contents

Part I

Foreword by James Gustave Speth page xi Preface xiii Framework and fundamentals 1 Overview and summary 3 1.1 Outline of the book 4 1.2 Rationale and motivations 9 1.3 Brief history and summary of sustainomics 20 1.4 Millennium development prospects and worldwide status 25 2 Sustainomics framework 31 2.1 Basic concepts and principles 31 2.2 Key elements of the sustainable development triangle 40 2.3 Integration of economic, social and environmental elements 46 2.4 Tools and methods for integrated analysis and assessment 55 2.5 Restructuring development and growth for greater sustainability 64 3 Economics of the environment 72 3.1 Human activities and the environment 72 3.2 Conventional project evaluation 73 3.3 Measuring costs and benefits 77 3.4 Basic concepts for valuing environmental costs and benefits 82 3.5 Multicriteria analysis 89 3.6 Discount rate, risk and uncertainty 91 3.7 Economy-wide policies and the environment 96 3.8 Appendix: Estimating and using shadow prices 106 4 Ecological and social aspects 111 4.1 Conceptual framework linking ecological and socioeconomic systems 111 4.2 Property rights, governance and ecological–social linkages 118 4.3 Environmental and social assessment 128

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Part II

Part III

Contents

Global and transnational applications 5 Global analytical applications 5.1 Climate change and sustainable development 5.2 Applying the sustainomics framework to climate change 5.3 Climate-change adaptation and mitigation 5.4 Global-level interactions between climate change and sustainable development 5.5 Greenhouse-gas-mitigation prospects in Sri Lanka 5.6 Real-options framework for carbon trading under uncertainty 6 International process applications: multilevel, multistakeholder, transdisciplinary dialogues 6.1 Global transdisciplinary scientific dialogue on climate change and sustainable development 6.2 Multilevel integration of millennium ecosystem assessment results and millennium development goals 6.3 Using the AIM to analyse MA–MDG links at the national and global levels 6.4 Dams and development: multilevel, multistakeholder dialogue 6.5 Evaluation of the Dams and Development Project (2001–2004) 6.6 Dams and Development Project evaluation, conclusions and results National and macroeconomic applications 7 National economy-wide applications 7.1 Historical evolution of ideas 7.2 Empirical evidence 7.3 Framework for analysis 7.4 Case study of Brazil – making long-term development more sustainable 8 Mathematical macromodel applications 8.1 Optimal growth models and sustainable development 8.2 Economic and non-economic costs and benefits of growth 8.3 An optimization model: Ecol-Opt-Growth-1 8.4 Ecol-Opt-Growth-1 model conclusions 8.5 Macroeconomic policies, second-best theory and environmental harm 8.6 Developing country case studies 8.7 Appendix A: The Ecol-Opt-Growth-1 model 8.8 Appendix B: Second-best nature of macroeconomic policies when environmental externalities are present

137 137 140 150 154 159 173 180 180 184 189 193 198 200 211 212 215 219 225 243 243 244 246 253 254 256 260 265

Contents

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Part IV

Computable general equilibrium modelling applications 9.1 Economy-wide cross-effects of social and environmental policies in Chile 9.2 Review of economic, social and environmental issues and policies 9.3 Interactions between social, environmental and economic policies 9.4 Chile case study conclusions 9.5 Economy-wide policies and deforestation in Costa Rica 9.6 Modelling approach 9.7 Main findings of the Costa Rica study 9.8 Appendix A: ECOGEM–Chile CGE model summary 9.9 Appendix B: Costa Rica CGE model summary

Sub-national sectoral and system applications 10 Energy-sector applications 10.1 Energy and sustainable development 10.2 Framework for sustainable energy development 10.3 Applying SED to power planning in Sri Lanka 10.4 Energy policy options 10.5 Assessing the sustainability of energy policies in South Africa 10.6 Making electricity development more sustainable in the UK 11 Transport-sector applications 11.1 Generic priorities for sustainable transport 11.2 Health-damage costs of air pollution in Sri Lanka 11.3 Traffic congestion – economic and environmental sustainability 11.4 Other options for reducing traffic congestion 11.5 Sustainable transport policy in Sri Lanka 12 Water-resource applications 12.1 Hydrological cycle and human actions 12.2 Water and development 12.3 Sustainable water-resources management and policy (SWAMP) 12.4 Management of groundwater depletion and saline intrusion in the Philippines 12.5 Policy implementation issues 12.6 Simple water filtration method for cholera prevention in Bangladesh 12.7 Appendix: Economic costs of producing water 13 Ecological and agricultural system applications 13.1 Sustainable management of tropical forests 13.2 Valuing forest ecosystems in Madagascar 13.3 Agriculture and climate change

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269 269 272 280 288 289 292 299 303 306 313 313 321 333 338 343 350 355 355 357 364 377 385 391 391 395 402 406 413 416 420 424 424 434 441

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Part V

13.4 Climate impacts on agriculture in Sri Lanka 13.5 Appendix: Models used for tropical forest valuation Resource-pricing-policy applications 14.1 Sustainable pricing policy (SPP) 14.2 Extensions of the basic model 14.3 Calculating economically efficient prices based on strict LRMC 14.4 Adjusting efficient prices to meet other objectives 14.5 Sustainable pricing of water resources 14.6 Appendix A: Optimal energy pricing 14.7 Appendix B: Demand analysis and forecasting

Project and local applications 15 Project applications 15.1 Small hydro-projects and sustainable energy development in Sri Lanka 15.2 Main findings of small hydro study 15.3 New and renewable energy projects: case study of solar photovoltaics 15.4 Sustainable rural electrification based on renewable energy 15.5 Evaluating a typical water supply project in a poor African village 16 Local applications – hazards, disasters and urban growth 16.1 Sustainable hazard reduction and disaster management (SHARM) 16.2 The 2004 Asian Tsunami – a preliminary assessment 16.3 Sustainability of long-term growth in Asian cities 16.4 Urban vulnerability, natural hazards and environmental degradation 16.5 Making urban development more sustainable in North America and Europe References Index

444 456 460 460 467 475 480 486 490 496 503 503 508 512 519 535 544 544 554 569 578 583 588 631

Foreword

Sustainable development is the foremost challenge to humanity in the twenty-first century. It affects every human being on the planet, and therefore we are all stakeholders. Traditional development has focused on material-based economic growth to overcome problems such as poverty, hunger, sickness and inequality. However, despite impressive progress during the last century, especially in the OECD and middle-income countries, these issues have grown worse in most of the poorest countries, and even among poorer communities in the industrial world. New challenges, such as environmental degradation, violent conflicts, climate change and runaway globalization, could exacerbate problems and make them unmanageable. At the global level, several thousand leading scientists in the United Nations Intergovernmental Panel on Climate Change (IPCC) have clearly confirmed that human activities that emit greenhouse gases are leading to potentially catastrophic global warming. Similarly, the recent Millennium Ecosystem Assessment, commissioned by UN Secretary General Kofi Annan and written by foremost ecologists, has chronicled the steady decline of ecosystem services, which support all life on the planet. They have urged early action to reverse this alarming trend. Yet, the alleviation of poverty among billions (who eke out their existence on less than one dollar a day) will require continued economic growth in those areas. Maintaining this balance among economic, social and environmental needs is the essence of sustainable development. The powerful technologies and forces we have unleashed may have increasingly unforeseeable and unmanageable consequences. We need to act with the prudence and wisdom suggested in Antoine de Saint Exupery’s The Little Prince: The fox said to the little prince: Men have forgotten this truth, but you must not forget it. You remain responsible, forever, for what you have tamed.

Therefore, Professor Munasinghe should be commended for writing a comprehensive, concise and clear volume that offers an immediate and practical path for making current development more sustainable, by applying the sustainomics framework. He demystifies the complexities of sustainable development with a critical and probing analysis. This book is unique in not only presenting an easily understandable and rigorous conceptual framework, but also in illustrating its practical applications using a wide range of empirical case studies. Professor Mohan Munasinghe first set out the basic principles of sustainomics at the 1992 Earth Summit in Rio de Janeiro. This volume expands on that base, and describes the careful analysis and rigorous testing of the framework during the past 15 years. Key elements of xi

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sustainomics include the fundamental approach of ‘making development more sustainable’ (MDMS); the balanced applications of Mohan’s widely recognized sustainable development triangle (with social, economic and environmental dimensions); better integration by transcending conventional boundaries (imposed by discipline, space, time, stakeholder viewpoints and operational needs); and practical application of innovative methods and tools throughout the full cycle (from data gathering to policy implementation and feedback). The methodology is elucidated with a number of practical case studies that are relevant over a wide range of geographic and time scales, countries, sectors, ecosystems and circumstances. In this book, Mohan brings together a wide range of skills. As a respected and award winning researcher, his analysis is rigorous and well documented. As a senior decision maker and manager with over 35 years of experience in the development arena, his advice is eminently practical. Finally, as a veteran university professor with an enviable record of publications, he presents his arguments lucidly and convincingly. To conclude, this text, written by a leading world authority on sustainable development, is an invaluable resource for students, researchers, development practitioners, policy analysts, public and private sector decision makers and, indeed, all concerned citizens. Professor James Gustave Speth Dean, School of Forestry and Environmental Studies, Yale University, and former Administrator, United Nations Development Program

Preface

This book is the sixth major volume in the Munasinghe Institute of Development (MIND) series on growth and sustainable development. Earlier volumes are listed at the front of this publication. A range of ideas about addressing the complex problems of sustainable development and poverty are set out in this text. Therefore, the reader may find some relevant background information helpful in understanding and interpreting my viewpoint. Physics and engineering were my first loves, and they sustained me all the way through a Ph.D. However, the lure of development was hard to resist, and this led me to pursue concurrently a post-graduate degree in development economics. This focus on the issues of poverty and development has continued ever since, and I have had no cause to regret the choice. Early work in the development area, during the early 1970s, helped me to concentrate on development planning and natural-resource management (especially energy and water) – amidst the ‘limits to growth’ debate and the first oil crisis. Although the concept of sustainable development was not known at the time, much of this initial work on marginal cost pricing, integrated resource planning and macroeconomic modelling was not only based on sound economic principles, but also included important social and environmental considerations, including poverty, equity and externalities. From the mid 1980s, my efforts shifted more towards environmental and natural-resource issues and their links with macroeconomic policies and poverty. With the publication of the Bruntland report in 1987, I began to focus on forming a better understanding of the new concept of sustainable development. The core framework of sustainomics was developed from around 1990, and now draws on more than 15 years of direct applications. Thus, the bulk of this book relies on work carried out since 1990. At the same time, sustainomics also makes use of previous research, where the issues, principles and policy options involved are still relevant. Some of the broader development insights, concepts and case studies in this volume are based on over 35 years of professional work. During this period, hands-on involvement in designing and implementing projects and policies in a variety of countries helped to build up practical experience in development activities. Meanwhile, continuing research and teaching sharpened my analytical insights. The basic foundation for intellectual growth was, of course, the preceding two decades of formal education, as well as the subconscious absorption of knowledge whilst growing up amidst the problems of development in Sri Lanka. To summarize, I have learned about development whilst playing many roles – be it as a student or teacher, researcher or field practitioner, policy analyst or decision maker. xiii

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Two major international events (i.e. the 1992 UN Earth Summit in Rio de Janeiro and the 2002 UN World Summit on Sustainable Development (WSSD), in Johannesburg) provided major impetus for two seminal publications (Munasinghe, 1992a, 2002a). The first paper set out the conceptual framework for sustainomics, based on the results of a major World Bank research programme that I led. At this time, the Vice Presidency for Environmentally and Socially Sustainable Development was established in the Bank, with the sustainable development triangle as its official logo. Shortly afterwards, some senior colleagues and I presented an important policy paper on Economy-wide Policies and the Environment to the Bank’s Board of Executive Directors, proposing policy remedies to address the adverse environmental and social impacts of structural adjustment programmes. The findings were then presented to the world’s finance ministers at a special seminar during the World Bank–International Monetary Fund 50th anniversary celebrations in Madrid, in 1994. Subsequently, my 2002 paper at WSSD elaborated on the initial sustainomics framework – based on a range of practical applications and lessons learned during the intervening decade. Clearly, sustainomics is not the creation of one person. Isaac Newton’s classic remark about ‘seeing further by standing on the shoulders of giants’, is most appropriate.1 Thus, sustainomics is a practical transdisciplinary framework (or ‘transdiscipline’) that makes use of my own ideas as well as many existing concepts, methods and tools developed by others – gladly acknowledged in the text. Such an eclectic approach is necessary because sustainable development is so broadly defined and vast in scope that it cannot possibly be dealt with by any single traditional discipline. Furthermore, there is no need to ‘re-invent the wheel’, when practical techniques and solutions are already at hand. Chapter 1 describes the main current rationale for writing this book. However, the original motivation that led to the neologism ‘sustainomics’ was more basic – simply the lack of a discipline or practical framework that focused explicitly on sustainable development problems in a policy-relevant manner. The first basic principle of sustainomics – making development more sustainable – was a practical reaction to the endless (and ongoing) theoretical debate on the ultimate definition of sustainable development. It motivates and validates those who wish to address urgent issues such as poverty and hunger immediately. The second core element – balanced treatment of the sustainable development triangle – was prompted by the lively discussions that took place in the run-up to Rio 1992, about how the ‘three pillars’ (environment, economy and society) might be integrated within development policy. It emphasizes that the sides and interior of the triangle (representing interaction among the three pillars) are as important as the three vertices. The third basic idea of transcending traditional boundaries (of discipline, space, time, etc.) has been around for many years, and proved quite appropriate for sustainomics. Finally, the kitbag of sustainomics methods and models includes some key policy-focused tools, such as the Action Impact Matrix (AIM), Issues-Policy Transformation Mapping (ITM) and Policy Tunnelling, which were developed specifically in the context of sustainomics. Others, such as sustainable development assessment (including cost–benefit analysis and environmental and social assessment), environmental valuation, green accounting, various macroeconomic 1

Lohne, J. (1965). ‘Isaac Newton: the rise of a scientist’, Notes and Records of the Royal Society London, 20, 125–39.

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and sectoral models, etc., were borrowed from other disciplines, or adapted from existing material. The empirical case studies are designed to be not only rigorous applications of the theory, but also practical and policy-focused. The extensive reference list should be useful to those who wish to research specific topics further. A brief word is appropriate here about the creation of the Munasinghe Institute for Development (MIND) in the year 2000. Working many years abroad within the UN system provided me with unique opportunities and insights. Nevertheless, I felt that I could improve my understanding of development problems and contribute more by taking early retirement and returning to live and work in Sri Lanka. This is a key decision I do not regret, because the view from Colombo is refreshingly different from the ‘Washington Consensus’ perspective. The outcome was MIND, a small non-profit research centre based in Sri Lanka, whose official logo is the sustainable development triangle, and whose motto is ‘making development more sustainable’. A balanced South–North partnership, built on mutual respect and cooperation, is essential to save the planet. To facilitate this process, MIND is building capacity in the South, and fostering both South–South and South–North collaboration to address sustainable development issues. During the course of this intellectual journey, I have benefited from my association with a wide range of people, each of whom has contributed generously to my understanding of development issues in his (or her) own way. While the core framework presented in the first few chapters of this book are based mainly on my own papers, the case studies have benefited greatly from ideas in selected co-authored publications. The list of names of the many erudite colleagues I have collaborated with over the years is far too numerous to set out here, but among them special thanks are owed to those with whom I have had the privilege of co-authoring journal articles and books that are the sources of material on which parts of this volume are based. They range from young students and researchers to eminent experts and Nobel prize winners. Working with them has enriched my professional growth and deepened my insights into the problems of development. Their valuable contributions are explicitly acknowledged in the relevant chapters. The honour list includes: Kenneth Arrow, Caroline Clarke, Matthew Clarke, William Cline, Wilfrido Cruz, Carlos de Miguel, Chitrupa Fernando, Claudio Ferraz, Sardar Islam, Susan Hanna, Paul Kleindorfer, Randall Kramer, Karl-Goran Maler, Jeffrey McNeely, Peter Meier, Robert Mendelsohn, Sebastian Miller, Risako Morimoto, Raul O’Ryan, Annika Persson, Walter Reid, Niggol Seo, Ronaldo Seroa da Motta, Narendra Sharma, Walter Shearer, Joseph Stiglitz, Osvaldo Sunkel, Rob Swart, Jeremy Warford and Carlos Young. I am equally grateful for the kind courtesies and good wishes extended by the following international journals in which relevant papers have appeared: Ambio, Conservation Ecology, Ecological Economics, Ecological Economics Encyclopedia, Encyclopedia of Earth, Environment and Development Economics, International Journal of Ambient Energy, International Journal of Environment and Pollution, International Journal of Global Energy Issues, International Journal of Global Environmental Issues, Land Use Policy, Natural Resources Forum, Natural Resources Journal, Proceedings of the IEEE, The Energy Journal, World Bank Economic Review and World Development.

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Thanks are also due to the following institutions who have published books and monographs I have authored, from which material is drawn: Asian Development Bank (ADB), Asian Pacific Economic Cooperation (APEC), Beijer International Institute of Ecological Economics, Cambridge University Press, Butterworths-Heinemann Press, Edward Elgar Publishing, Intergovernmental Panel on Climate Change (IPCC), International Decade for Natural Disaster Reduction (IDNDR), International Society of Ecological Economics (ISEE), Johns Hopkins University Press, Organization for Economic Cooperation and Development (OECD), Sri Lanka Association for the Advancement of Science (SLAAS), United Nations Development Programme (UNDP), United Nations Environment Programme (UNEP), United Nations University (UNU), Westview Press, World Bank (WB) and International Union for Conservation of Nature (IUCN). Generations of students have helped to sharpen my concepts and logical thinking over the years. I would like to express my gratitude for the valuable feedback provided by students and faculty from the following academic and research institutions where I have given courses or lectures on various aspects of sustainable development in recent years: American University, USA; Asian Institute of Technology, Thailand; Boston University, USA; Cambridge University, UK; China Meteorological Administration, China: Colombo University, Sri Lanka; Concordia University, Canada; Federal University of Rio de Janeiro, Brazil; Gotenberg University, Sweden; Groningen University, Netherlands; Harvard University, USA; Indian Institute of Management (Calcutta), India; Indira Gandhi Institute of Development Research, India; Institute of Economic Growth, India; Institute of Social and Economic Research, India; Japan Development Bank, Japan; Massachusetts Institute of Technology, USA; Moratuwa University, Sri Lanka; Oxford University, UK; Peking University, China; University of Pennsylvania, USA; Peradeniya University, Sri Lanka; Ritsumeikan Asia Pacific University, Japan; Sorbonne University, France; State University of New York, USA; Tellus Institute, USA; TERI University, India; Tsinghua University, China; United Nations University, Japan; Wuppertal Institute, Germany; Yale University, USA. I am deeply indebted to the following, who provided detailed and insightful comments and helpful material: Johannes Opschoor, Rob Swart and Harald Winkler. I also thank the following for useful suggestions and advice: Michael Chadwick, Nazli Choucri, Cutler Cleveland, Shelton Davis, Surendra Devkota, Sytze Dijkstra, Chitru Fernando, Prasanthi Gunawardene, Anders Hansen, Jochen Jesinghaus, Steven Lovink, Risako Morimoto, Eric Neumayer, John O’Connor, Paul Raskin, Terry Rolfe, Fereidoon Sioshansi, Nimal Siripala, Jeremy Warford and Robin White. The MIND team who helped to prepare this manuscript provided invaluable assistance, for which I am most grateful. They include: Nishanthi De Silva, Yvani Deraniyagala, Irusha Dharmaratna, Priyangi Jayasinghe and Sudarshana Perera. Last, but not least, my wife Sria deserves special praise for her advice and steadfast support, and for putting up with the many impositions and pressures arising from the preparation of this book. Support provided by my children Anusha and Ranjiva and my mother Flower Munasinghe were also much appreciated.

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All my generous benefactors deserve full credit for their valuable contributions to the ideas expressed in this book. Any errors, omissions, shortcomings and misinterpretations are my own responsibility. I hope that the book will appeal to a wide audience, including students, researchers, teachers, policy analysts, development practitioners, public- and private-sector decision makers, concerned citizens and all stakeholders. To conclude, sustainomics is a preliminary framework and is, as yet, incomplete. It is like a giant jigsaw puzzle, with some gaps and pieces that do not quite fit. Nevertheless, it does seem to provide a promising and practical start, which is allowing the bigger picture to emerge. My earnest hope is that other practicing and potential ‘sustainomists’ will step forward to correct any errors, reconcile inconsistencies and fill in the empty spaces in the framework, in the process of moving towards the ultimate goal of sustainable development. The final take-home message is optimistic: although the problems are serious, an effective response can be mounted, provided we begin immediately. Sustainomics can help to show us the first practical steps in making the transition from the risky business-as-usual scenario to a safer, and more sustainable, future.

Part I Framework and fundamentals

1 Overview and summary

This book recognizes that sustainable development is a primary challenge of the twenty-first century (with poverty alleviation as the main goal), and sets out a framework called ‘Sustainomics’ developed over the past 15 years to meet that challenge. Sustainable development is broadly defined here as ‘a process for improving the range of opportunities that will enable individual human beings and communities to achieve their aspirations and full potential over a sustained period of time, while maintaining the resilience of economic, social and environmental systems’. The main message of this volume is optimistic – although the problems are serious, an effective response can be mounted, provided we begin immediately. Sustainomics seeks to show us the first practical steps in making the transition from the risky business-as-usual scenario to a safer and more sustainable future. Sustainomics is ‘a transdisciplinary, integrative, comprehensive, balanced, heuristic and practical framework for making development more sustainable’. Unlike other traditional disciplines, it focuses exclusively on sustainable development. Thus, the main principle of the framework seeks to make ongoing and future development efforts more sustainable, as a first step toward the ultimate goal of sustainable development. Other key principles stress: (a) balanced consideration of the three dimensions of the sustainable development triangle (social, economic and environmental); (b) better integration by transcending conventional boundaries imposed by discipline, space, time, stakeholder viewpoints and operational needs; and (c) practical application of innovative methods and tools throughout the full cycle from data gathering to policy implementation and feedback. This volume also seeks to illustrate clearly the methodology with empirical case studies that are practical and policy-relevant over a wide range of geographic and time scales, countries, sectors, ecosystems and circumstances. Every application does not necessarily give equal weight to all elements of the triangle (i.e. social, environmental and economic). Many cover all three aspects, while others primarily address two aspects (e.g. economic and environmental), or a single aspect (e.g. economic cost–benefit analysis, social multistakeholder consultative process, etc.), with the other aspects covered less prominently. In general, the book shows how a broad array of sustainomics-compatible methods and tools could be applied simply and practically to a variety of problems, to make development more sustainable. 3

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Framework and fundamentals

I have tried to make the book both accurate and readable. However, because of its wide coverage and length, some parts may seem complex and others too simple, depending on the academic training and disciplinary background of the reader. A fair balance is maintained between theory and applications, recalling the famous rebuke by Nobel Laureate Wassily Leontief (Leontief, 1982): ‘Page after page of professional economic journals are filled with mathematical formulas leading the reader from sets of more or less plausible but entirely arbitrary assumptions to precisely stated but irrelevant theoretical conclusions.’ Generally, the analytical sections are rigorous but relatively free of technical jargon, while mathematical and other details are provided in appendixes. The case studies have been simplified to show, as clearly as possible, the practicality and policy-relevance of the underlying principles involved. They are presented in decreasing order of geographic scale – from global to local applications. The extensive bibliography should be useful to those who wish to research specific topics further. I hope that the book will appeal to a wide audience, including students, researchers, teachers, policy analysts, development practitioners, public and private sector decision makers, concerned citizens and all stakeholders. To conclude, sustainomics is put forward as an innovative transdisciplinary framework (or transdiscipline), based on a holistic set of key principles, theories and methods. It draws on many other approaches and techniques, because no single traditional discipline can cover the vast scope and complexity of sustainable development issues. The advantages and shortcomings of sustainomics are frankly laid out, with the expectation that future contributions by other potential ‘sustainomists’ will rapidly build on the strengths, remedy gaps and inconsistencies, and further flesh out the initial framework and applications. 1.1 Outline of the book Part I of the book contains four chapters covering the introduction and fundamentals. Chapter 1 provides a broad overview of the entire volume. The first section outlines the various chapters and provides a road map for the reader. Next, we set out the rationale and motivations for the book, including key sustainable development challenges (especially poverty), major global agreements on sustainable development, lessons of history and future scenarios and a vision for a practical way forward. A brief history and introduction to the fundamental elements of sustainomics are provided, followed by a review of key ideas. The chapter ends with selected information on the status of modern development. Chapter 2 lays out the basic principles, concepts and methods of sustainomics in greater detail. A practical approach based on making development more sustainable, or MDMS, is described as an alternative to pursuing abstract definitions of sustainable development. The sustainable development triangle, comprising the social, economic and environmental domains, is introduced, and the driving forces and concepts of sustainability underlying each viewpoint are explained. The integration and synthesis of these three viewpoints is facilitated by two complementary approaches, based on the concepts of optimality and durability. The poverty–equity–population nexus and linkages between economic efficiency and social equity are discussed. A variety of practical analytical tools are outlined to


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implement the sustainomics framework – including the Action Impact Matrix (AIM), sustainable development assessment (SDA), cost–benefit analysis (CBA), multicriteria analysis (MCA), etc. It is important to select relevant, time and location specific indicators of sustainable development. The need to harmonize development with nature, and restructure the pattern of growth is explained, especially in developing countries, where poverty alleviation will require continued increases in income and consumption. In Chapter 3, we explore the economy–environment interface (and related social linkages). Economic CBA is a key element of SDA and the project cycle. Basic concepts of CBA are set out, including decision criteria, efficiency and social shadow pricing and measurement of costs and benefits. Practical techniques for economic valuation of environmental assets and services play a key role in incorporating externalities into traditional CBA. When such economic valuation is difficult, MCA helps to make trade-offs among disparate objectives. Key issues, such as discounting, risk and uncertainty, are discussed. The twoway links between economy-wide (macroeconomic and sectoral) policies and environment (and social) issues are outlined. The incorporation of environmental considerations into the conventional system of national accounts is explained. Chapter 4 expands on the social and ecological interlinkages that play a key role in determining the use of natural resources. The Millennium Ecosystem Assessment (MA) conceptual framework and cyclic interaction between the ecological and socioeconomic domains is summarized, including the main ecosystem services which sustain key components of human well-being. Ecological cycles involving birth–growth–decay–death– regeneration help us understand ecosystem dynamics. Property rights regimes determine how socioeconomic forces interact with environmental resource, especially in the case of traditional societies and native peoples, who are heavily dependent on ecological resources, as well as the landless poor, who subsist in degraded areas. Finally, environmental and social assessments are described as important tools that complement economic assessment (CBA) – all three are key elements of SDA. Next, we turn to applications of sustainomics at various scales: global and transnational, national and macroeconomic, sub-national sectoral and system, project and local. Part II of the book contains two chapters (5 and 6) with case studies covering the global and transnational levels. In Chapter 5 the sustainomics framework is applied to study the circular linkage between two global-level issues – climate change and sustainable development. The role of adaptation and mitigation are analysed, and several applications are provided. First, alternative climate change mitigation response strategies are assessed in terms of optimality and durability. Next, we examine the interplay of equity and efficiency in joint implementation (JI) and emissions trading, between Annex 1 and non-Annex 1 countries. The final case study describes how climate change might interact with sustainable development at the national level – by analysing greenhouse gas (GHG) mitigation prospects in Sri Lanka. Chapter 6 examines a unique transdisciplinary, international scientific dialogue within the Intergovernmental Panel on Climate Change (IPCC), describing how researchers are analysing climate change and sustainable development links. Then, the AIM tool is used to

6


explore two-way linkages between two international activities – the millennium development goals (MDGs) and the findings of the MA. Finally, we examine the practical functioning of a transnational, multistakeholder, multilevel consultative process, involving the UNEP Dams and Development Programme (DDP). Part III of the book comprises three chapters (7, 8 and 9), covering case studies of sustainomics at the country-wide and macro levels, which deal with a wide range of countries, policy issues and models. Chapter 7 reviews past research on the sustainability of long-term economic growth, including economy–environment linkages. Some stylized facts about environmental and social impacts of growth-oriented macroeconomic policies are summarized. Unforeseen economic imperfections can interact with growth to cause environmental and social harm. An environmental-macroeconomic analysis confirms that second-best remedial measures could help to limit the damage. Environmental concerns may be introduced into the standard static IS-LM macroeconomic model. The role of green accounting and concepts such as genuine savings are discussed. The AIM approach plays a key role in environmentalmacroeconomic analysis. A ‘policy-tunnelling’ model shows how elimination of economic imperfections permits continued growth while limiting environmental and social harm. Finally, some of these ideas are illustrated through a case study of Brazil. A combination of sectoral and macroeconomic models are used to examine the effects of the growthoriented strategy pursued by the Brazilian government during the past decades, on a range of sustainable development issues including poverty, employment, urban pollution and deforestation in the Amazon region. Ideas for future research are discussed. Chapter 8 explores two different theoretical approaches to making development more sustainable at the national macroeconomic level. The literature on the relationship between optimization and sustainability in growth models is reviewed. First, a sustainomicscompatible mathematical model examines the conditions under which development paths, focusing on optimal economic growth, might also be made more sustainable. The model is solved numerically using stylized data. Second, a theoretical model looks at the circumstances that may justify the use of second-best adjustments to macroeconomic policies, to compensate for pre-existing economic distortions that give rise to environmental harm. Three developing world examples (Botswana, Ghana and Morocco) show how macroeconomic polices might combine with local imperfections to harm the environment, and appropriate remedial measures are discussed. Chapter 9 focuses on computable general equilibrium (CGE) models. First, we apply the ECOGEM model to assess economic, environmental and social policy linkages in Chile. The model systematically and holistically analyses different economy-wide policies and their impact on the Chilean economy. It combines different environmental and social policies so as to enhance positive cross-effects or to mitigate the negative side effects of any single policy. Complex interrelations between the diverse sectors and agents of the economy are captured. Winners and losers are identified, but the results obtained are not always obvious, i.e. indirect effects are also relevant. In the second example, a static CGE model is applied to study the effects of macroeconomic policies on deforestation in Costa


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Rica. The results support the more conventional partial equilibrium approach that establishing property rights tends to decrease deforestation, because such rights allow forest users to capture the future benefits of reduced logging damage today. Findings about effects of discount-rate changes also parallel results of partial equilibrium models – higher interest rates promote deforestation, and vice versa. The CGE approach also identifies the indirect effects of intersectoral links, and shows the importance of pursuing sectoral reforms in the context of growth. A dynamic CGE model of Costa Rica, where the value of forest conservation, capital accumulation and interest rate are endogenized, gives the same results as the static CGE model. Part IV of the book contains five chapters (10 to 14) describing case studies and applications of sustainomics at the sub-national and meso levels within several countries – involving energy, transport, water, ecological and agricultural systems and resource pricing policies. In Chapter 10, we begin with a general review of links between energy and sustainable development, including a worldwide assessment of energy sector status and issues. Next, the sustainomics approach is used to develop a comprehensive and integrated conceptual framework for an energy-related decision-making framework called sustainable energy development (SED), which identifies practical sustainable energy options by taking into account multiple actors, multiple criteria, multilevel decision making and policy constraints. The methodology is applied to demonstrate how social and environmental externalities could be incorporated into traditional least-cost power-system planning in Sri Lanka, using both CBA and MCA. The study is relatively unique in its focus on assessing environmental and social concerns at the system-level planning (including technology choices among hydro, oil, coal and renewable-energy-based generation), as opposed to the more usual practice of carrying out such analyses only at the project level. Sustainable energy policies for Sri Lanka are identified. Another case study applies SED to the South African energy sector, using MCA to assess the social, economic and environmental trade-offs arising from policy options relating to electricity supply and household energy use. Finally, long-term UK electricity expansion options are examined, to show that decentralized energy may be more sustainable than centralized generation. Chapter 11 starts by reviewing generic sustainable transport priorities. Then we examine how transport policy could be made more sustainable in Sri Lanka, including the analysis of fuel pricing policy, alternative fuel choices and a range of transport projects. Two classic externalities are discussed. First, the detrimental impact on health from local air emissions are estimated using the benefit transfer method, and the specific health benefits of introducing unleaded petrol are assessed. Second, the effects of traffic congestion in the city of Colombo are studied, including estimation of the cost of time wasted. Several specific infrastructure projects and other measures for reducing congestion are analysed, and an overview is provided of sustainable transport policy options for Sri Lanka. Chapter 12 explores how to make water resource management more sustainable. The first section describes the natural hydrological cycle and how interventions have affected it. Next, water and development linkages are examined, including a review of the global status

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of water resources, water shortages and rising costs, poverty issues and sustainable livelihoods. A comprehensive framework for sustainable water resources management and policy (SWAMP) is outlined, which parallels the SED approach of Chapter 10. The SWAMP methodology is practically applied to a typical water resources project involving groundwater for urban use in Manila, Philippines. The case study analyses the effects of environmentally harmful externalities like aquifer depletion, saltwater intrusion along the coast and land subsidence, and then identifies remedial policy measures. Finally, another case study demonstrates a simple, low-cost, socially acceptable and environmentally desirable approach to purifying drinking water and reducing waterborne diseases that has yielded significant economic, social and environmental gains to poor villagers in Bangladesh. Chapter 13 sets out case studies dealing with both natural and managed ecological systems – i.e. forests and agriculture, respectively. First, we analyse the management of megadiverse natural ecosystems in rainforests to identify generic policies that make forest management more sustainable. Next, a case study of Madagascar is presented to achieve a better understanding of the specific environmental and socioeconomic impact of national parks’ management policies on tropical forests. Relevant policy implications are drawn. Various techniques are used to value damage economically to forests and watersheds, timber and non-timber forest products, impact on local inhabitants and biodiversity and ecotourism benefits. In a second case study, we examine the potential impact of climate change on managed ecosystems (agriculture) in Sri Lanka. A Ricardian model is used to estimate the past effects of natural variations in both temperature and precipitation. Several scenarios of future climate change are imposed to assess future agricultural production. The harmful impact of rising temperatures generally dominate the beneficial effects of increased precipitation. Policy conclusions are drawn for sustainable agricultural policy in Sri Lanka. Chapter 14 examines natural-resource pricing policy issues within a national economy – the economics of both renewable and non-renewable resources are discussed. The principles of sustainable pricing policy (SPP) are explained and applied to energy, based on the sustainable energy development framework (Chapter 10). First, economic principles are used to determine efficient energy prices, which lead to economically optimal production and consumption of energy. Second, environmental aspects may be incorporated by economically valuing relevant impacts (Chapter 3). Finally, efficient prices may be made more sustainable by adjusting for economic second-best distortions, social consideration, such as affordable (subsidized) prices to meet the basic needs of the poor, and other general policy objectives such as regional or political considerations. The closing section describes how the SPP framework might be used for pricing of other natural resources, such as water, and examines water-specific issues. Part V of the book contains two chapters (15 and 16) dealing with case studies and applications of sustainomics at project and local levels, which cover topics such as hydropower, solar energy, water supply, sustainable hazard reduction and disaster management and urban growth. Chapter 15 commences with the SDA of small hydro-projects in Sri Lanka, by applying MCA to economic, social and environmental indicators. The second case study analyses


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new and renewable energy projects and national energy policy in a typical developing country. It highlights the use of different policy tools (including the interlinked shadow and market prices) to influence human behaviour and ensure more sustainable energy use – based on solar photovoltaic (PV) energy for agricultural pumping. Then, rural electrification projects in Sri Lanka are analysed with a focus on new and renewable energy technologies, and rural energy priorities are set out. Chapter 16 explains how natural hazards become major disasters because of heightened vulnerability, often due to prior damage inflicted by unsustainable human activities. A practical framework is presented for mainstreaming sustainable hazard reduction and management (SHARM) into national development – involving the stages of relief, rehabilitation and reduction (planning, preparedness and prevention). The two-way linkages between hazards and sustainable development are analysed. These ideas are illustrated by a case study that assesses the impacts of the 2004 Asian Tsunami in India, Indonesia, Maldives, Sri Lanka and Thailand. A comparison of the Tsunami impacts on Sri Lanka and Hurricane Katrina on New Orleans raises important questions about the role of social capital in coping with disasters. Issues concerning the sustainability of long-term growth in Asian cities are described, including policy options to address these problems – especially in the rapidly expanding mega-cities. The vulnerability of cities to natural hazards and environmental degradation is analysed and illustrated through a case study of floods in Rio de Janeiro. Finally, we examine two examples of how urban development is becoming more sustainable in developed nations – in Canada and the European Union. 1.2 Rationale and motivations This section summarizes several important motivations underlying this book.

1.2.1 Addressing key sustainable development challenges today The first and main rationale is the urgent need to address key sustainable development challenges of the twenty-first century. Poverty, inequity and human well-being The key sustainable challenges that arise are as follows (see also Box 1.1). *

*

*

*

Alleviating poverty for the 1.3 billion people who live on less than $1 per day and the 3 billion people who live on less than $2 per day. Providing adequate food, especially for the 800 million people who are malnourished today – this will require food production to double in the next 35 years without further land and water degradation. Supplying clean water to the 1.3 billion people who live without clean water, and providing sanitation for the 2 billion people who live without sanitation. Supplying adequate energy for basic needs, and providing access to the 2 billion people who live without electricity.

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*

Providing a healthy environment for the 1.4 billion people who are exposed to dangerous levels of outdoor pollution and the even larger number (especially women and children) exposed to dangerous levels of indoor air pollution and vector-borne diseases. Providing safe shelter for those who are vulnerable to natural disasters and those that live in areas susceptible to civil strife.

*

The extreme poverty and deprivation captured by these statistics are further highlighted by high levels of global inequality. For example, the richest 20% of the world population currently consumes about 60-fold more than the poorest 20%. Highly inequitable income

Box 1.1 Summary of Millennium Development Goals (MDGs) The UN Millennium Development Goals provide a basis for measuring global progress toward sustainable development. In 2000, all countries agreed on eight development goals that would serve as targets for 2015. Eradicate extreme poverty and hunger, by halving the population (1) whose income is less than a $1/day and (2) who suffer from hunger, between 1990 and 2015. Goal 2: Achieve universal primary education, by ensuring that all children will complete full primary schooling by 2015. Goal 3: Promote gender equality and empower women, by eliminating gender disparity in primary and secondary education, preferably by 2005 and in all levels of education no later than 2015. Goal 4: Reduce child mortality, by lowering the under-five mortality rate by two-thirds between 1990 and 2015. Goal 5: Improve maternal health, by reducing maternal mortality rates by 75% between 1990 and 2015. Goal 6: Combat HIV/AIDS, malaria and other diseases, by reversing the spread of HIV/ AIDS and the incidence of malaria and other major diseases by 2015. Goal 7: Ensure environmental sustainability, by (1) integrating sustainable development into country policies and programmes and reversing the loss of environmental resources; (2) halving the population without sustainable access to safe drinking water and basic sanitation by 2015; and (3) achieving a significant improvement in the lives of at least 100 million slum dwellers by 2020. Goal 8: Develop a global partnership for development, by (1) improving trading and financial systems; (2) addressing the special needs of the least-developed countries; (3) addressing the special needs of landlocked countries and small island developing states; (4) dealing comprehensively with the debt problems of developing countries; (5) developing and implementing strategies for decent and productive work for youth; (6) providing access to affordable, essential drugs in developing countries; and (7) making new technologies available in cooperation with the private sector, especially information and communications. Energy services, although not explicitly identified, are essential to achieve the MDGs (UNDP, 2005c). Goal 1:


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distributions also persist within many countries (World Bank, 2000). In Brazil and South Africa, the ratios of national income received by the richest and poorest 10% of the population are 53% and 42%, respectively. Corresponding figures for India and the USA are 10% and 14%. Globalization Globalization is a major sustainable development challenge. There are many benefits, but the focus here is on identifying potential risks in order to address the underlying problems. This phenomenon has been driven by two fundamental forces – underlying technological change, which has accelerated the integration of markets, and the freer movement of raw materials, goods, services, labour, capital, information and ideas. For example, during 1950 to 1998, world exports of goods increased 17-fold (from $311 billion to $5.4 trillion); the global economy expanded six-fold; international tourist arrivals increased 25-fold (from 25 million to 635 million); during 1970 to 1998 the number of transnational corporations grew eight-fold (from 7000 to 54 000); and during 1960 to 1998 the number of non-cellular telephone lines linked directly to the global phone network grew eight-fold (from 89 million to 838 million) (French, 2000). Globalization also implies a gradual weakening of the influence of individual national governments. While this process may improve opportunities for economic growth, recent research has pointed out that it fails to provide equal opportunities either across or within nations (Ehrenfeld, 2003). In addition, globalization is associated with significant social and environmental costs that are rarely assigned monetary values and often fall on the poor and disadvantaged, while the benefits accrue mainly to the wealthy. The environmental costs of globalization (due to pollution of air, land and water and the depletion of natural resources) are mostly associated with increased free trade across borders and industrial activities. Pollution may shift to (mainly developing) countries where environmental protection laws and property rights are not adequately enforced or do not exist. Meanwhile, the burden of global environmental issues like climate change will fall disproportionately on poorer countries that have contributed least to the problem. Furthermore, these countries are less well equipped to deal with such impacts due to lack of financial and technical resources (IMF, 2002). Biodiversity loss has worsened due to the wave of globalization and stimulation of unsustainable development activities, reduction of forests, over-fishing, land degradation, etc. (MA, 2005a). Loss of biodiversity in turn impacts on sustainable development, as it undermines ecosystem health and reduces resilience (Munasinghe, 1992a). For example, globalization has promoted monoculture agricultural practices that favour commercially successful crops and reduce the diversity of less successful crop varieties. The social costs of globalization often remain hidden and indirect before surfacing suddenly (Ahmad, 2005). Among many such social issues are growing inequity, social unrest, unemployment, dissolution of families and communities and instability of socioeconomic systems (Stiglitz, 2002). The widening of the gap between rich and poor is a frequent issue that is raised by many critics of globalization. Open borders for flow of capital

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and finished products combined with technological advancement has increased the power of multinational corporations and has given them enormous economic profits. However, these profits may not be fairly distributed between multinational corporations and workers (especially in developing countries). Inequity is worsened when seemingly borderless multinationals externalize costs of production in order to increase profits, while jeopardizing social and environmental resilience within borders. One of the main challenges that globalization poses concerns the inadequacy of current systems of governance to manage this new integrated world. Globalization permits positive as well as negative economic, environmental or social activity in one country to be transmitted to another – for example, an economic downturn or an upturn in the USA is easily felt in Latin America, or the economic ‘footprint’ of Japan may have a heavy influence on deforestation in South East Asia. At the same time, advances in information sharing and international communications may help to make development more sustainable. For example, the Global System for Sustainable Development based at MIT1 seeks to map information on sustainable development and make it widely accessible as a dynamic, distributed global knowledge network operating on the Internet (Choucri, 2003). Another example is the open source philosophy of Linux,2 which provides free operating system software. On the positive side, the rise of the General Agreement on Tariffs and Trade and the World Trade Organisation has led to a dramatic increase in world trade and a corresponding jump in standards of living. Elimination of trade barriers would generate global gains in economic growth in excess of US $750 billion per year (Commonwealth of Australia, 1999). The beneficial effects of competition stemming from globalization improve the position of all parties, with the potential for increased output as a result of the rationalization of production on a global scale, the spread of technology and competitive pressures for continual innovation on a worldwide basis (Micklethwait and Wooldridge, 2000) and economies of scale that can potentially lead to reductions in costs and prices. The result is a potential for greater human well-being throughout the world. Countries that have grown prosperous through extensive trade interactions are less likely to use armed conflict to resolve their differences. Trade and investment, and the economic growth they encourage, are very positive forces in reducing international tension. For less-developed countries, globalization offers access to foreign capital, global export markets and advanced technology, while breaking the monopoly of inefficient and protected domestic producers. Faster growth, in turn, promotes poverty reduction, democratization and higher labour and environmental standards (Lukas, 2000). In brief, globalization is not an inanimate process – it is controlled by people. Reform of the global institutional framework is needed, especially the World Bank, the International Monetary Fund, and the World Trade Organisation. Changes include better voting structures and representation (Stiglitz, 2006). Reforms should also increase transparency, limit conflicts of interest, improve accountability, enforce the international rule of law and enhance the ability of developing countries to participate meaningfully in decision making. The

1

See http://gssd.mit.edu/

2

See http://www.linux.org/


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sustainomics approach suggests that it will be possible to shape the forces of globalization for the greater good, based on rational analysis, good governance and ethics. Private–public balance Between 1985 and 1994, $468 billion worth of state enterprises were sold off to private investors, globally. However, with a few notable and highly controversial exceptions, governments have not been as eager to sell off their vast natural resource holdings, including forest lands, parks and waterways (Cole, 1999). Some economists argue that natural resources would be better managed economically and environmentally by the private owners than by governments. However, since non-use values of the resource have no monetary value, this may discourage owners from conserving the resource, leading to unsustainable overexploitation of the resource without considering the long-term benefits of conservation. Privatization of state property may provide a unique opportunity to address not only existing financial issues, but also environmental ones that are neglected due to a lack of investments or poor knowledge of new technology. However, unless a clear legislative framework is set up to deal with the problems under the new system, the profit-maximizing private sector may not invest the required amount of capital to minimize environmental impact and acquire environmentally friendly technology. Inadequate regulation may also cause social problems by permitting privatized providers of basic needs such as energy and water services to raise prices to levels that are not affordable by the poor (Chapter 14). Multinational organizations usually transfer modern, environmentally friendly technology and install advanced pollution control equipment in their plants. However, this may not be the latest technology, even though it is in compliance with the (lower) environmental standards in developing countries. These lower standards are due to two reasons. One is to attract more foreign capital from the international investment market, and the other is due to the delay in identifying and introducing new standards. Another problem may arise if the government agency usually involved in privatization of state-owned enterprises (SOEs) is mainly interested in generating a higher income from the transaction, rather than in solving any environmental problems. Lack of transparency in the privatization process will exacerbate such problems. Environmental damage Global environmental trends have reached a dangerous crossroads as the new century begins (Ayensu et al., 2000; IPCC, 2001d; Baille et al., 2004; MA, 2005a; UNEP, 2006; Worldwatch, 2001; WRI, UNDP, UNEP and World Bank, 2000). Signs of accelerated ecological decline have coincided with a loss of political momentum on environmental issues. This failure calls into question whether the world will be able to reverse these trends before the economy suffers irreversible damage. New scientific evidence indicates that many global ecosystems are reaching critical thresholds. The Arctic ice has already thinned by 42%, and 27% of the world’s coral reefs have been lost in the last 100 years, suggesting that some of the planet’s key ecological systems are in decline. Environmental degradation is also leading to more severe natural

14


disasters, which have cost the world $608 billion over the last decade – as much as in the previous four decades combined. One sign of ecological decline is the risk of extinction that hangs over dozens of species of frogs and other amphibians around the globe, due to pressures that range from deforestation to ozone depletion. With many life-support systems at risk of long-term damage, decisions need to be made whether to move forward rapidly to build a sustainable economy or to risk allowing the expansion in consumption, the increase in greenhouse gas emissions and the loss of natural systems that undermine future development. Even after a decade of declining poverty in many nations, 1.2 billion people lack access to clean water and hundreds of millions breathe unhealthy air. Poor people in developing countries are pushed to destroy forests and coral reefs in a desperate effort to raise living standards. Environmental degradation is increasing vulnerability to natural disasters – mainly among the poor. In 1998 to 1999 alone, over 120 000 people were killed and millions were displaced in regions such as India and Latin America, due to their inability to withstand disasters. Lack of land has led people to settle in flood-prone valleys and unstable hillsides, where deforestation and climate change have increased their vulnerability to disasters such as Hurricane Mitch, which produced economic losses of $8.5 billion in Central America in 1998 – equal to the combined GNPs of Honduras and Nicaragua. Unless fossil fuel use slows dramatically, the Earth’s temperature could rise as high as 6 degrees above the 1990 level by 2100, according to the latest climate models. Such an increase could lead to more extreme events, acute water shortages, declining food production and the proliferation of deadly diseases such as malaria and dengue fever, which will especially harm the poor. Conflict and competition for resources Violent conflict blights the lives of hundreds of millions of people. It is a source of systematic violations of human rights and a barrier to progress toward the MDGs. Poverty and the lack of progress toward the MDGs may themselves exacerbate conflicts. For many people in rich countries the concept of global insecurity is linked to threats posed by terrorism and organized crime. Meanwhile, the interaction between poverty and violent conflict in many developing countries is destroying lives on an enormous scale. Failure to build human security by ending this vicious cycle will have global consequences. In an interdependent world the threats posed by violent conflict do not stop at national borders. Development in poor countries is a key element in achieving global peace and collective security. The current approach may be overemphasizing military strategy and not paying adequate attention to addressing poverty and human security concerns. The nature of conflict has changed, and new threats to collective security have emerged. The twentieth century was defined first by wars between countries and then by cold war fears of violent confrontation between two superpowers. Now these fears have given way to fears of local and regional wars fought predominantly in poor countries within weak or failed states, and with small arms as the weapon of choice. Most of the victims in today’s wars are civilians. There are fewer conflicts in the world today than in 1990, but the share of


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those conflicts occurring in poor countries has increased – often arising from the struggle for valuable resources (like water, oil, gold, diamonds, etc.), and exacerbated by foreign interests. In an increasingly interconnected world, local conflicts could spread quickly. More effective international cooperation could help to remove the barrier to MDG progress created by conflict, creating the conditions for sustainable development and real human security. The human development costs of violent conflict are not sufficiently appreciated. In the Congo deaths attributable directly or indirectly to conflict exceed the losses sustained by Britain in the First and Second World Wars combined. In the Darfur region of Sudan, nearly two million people have been displaced because of conflict. Conflict undermines nutrition and public health, destroys education systems, devastates livelihoods and retards prospects for economic growth. Of the 32 countries in the low human development category as measured by the UNDP Human Development Index (HDI), 22 have had some conflict since 1990. Countries that have experienced violent conflict are far more likely to be performing well below the MDG projections for 2015 (Section 1.4). Of the 52 countries that are failing to reduce child mortality, 30 have experienced conflict since 1990. Such costs underline the need for conflict prevention, resolution and post-conflict reconstruction as three basic requirements for building human security, accelerating progress toward the MDGs and making development more sustainable. As indicated earlier, globalization and privatization could intensify competition for resources and lead to conflicts. Both international and national mechanisms need to be strengthened to prevent and manage conflicts. Due to the rising demand for goods and services, along with economic development, the level of extraction or utilization of natural resources increases. Higher demand and competition for oil, coal, water, land, forest products, recreational areas and other natural resources lead to long-run depletion of, and competition for, those resources – especially when there are no appropriate policies for sustainable utilization. Competition for scarce natural resources will intensify in the future due to the unsustainable present usage of natural resources. This issue is linked to the environmental harm problem discussed above. It will be necessary to invest more in research and development to identify more efficient methods of resource use to fulfil human requirements and find effective conservation measures. Furthermore, greater efforts need to be devoted to enhancing both international and national institutional mechanisms and management capacities to respond to the competition for natural resources and harm to fragile ecosystems. Promoting pluralistic, multistakeholder, multilevel consultation is important for resolving differences and avoiding conflicts (see Section 1.2.4 and Chapter 6). Poor governance Poor governance has caused the massive waste of resources which has hampered efforts to address sustainable development problems such as poverty, hunger and environmental degradation (Section 4.2). Corruption, inefficiency, greed, rape of natural resources and other manifestations of bad governance abound. Overcoming them is a major challenge for

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those who govern and are governed. Good governance needs to be participatory, consensus-oriented, accountable, transparent, responsive, effective and efficient, equitable, inclusive and must follow the rule of law. Among the key outcomes are that corruption is minimized, the views of minorities are taken into account, the most vulnerable in society participate in decision making and policy becomes responsive to the present and future needs of society. Where there is poor governance, there is more scope for corruption. An overview of corruption around the world demonstrates that its most common causes are economic in nature. Corruption thrives in the presence of excessive government regulation and intervention in the economy, substantial exchange and trade restrictions and complex tax laws. Corruption is further favoured by lax spending controls and when the government provides goods, services and resources at below-market prices (e.g. foreign exchange, credit, public utilities and housing, access to education and health facilities and access to public land). There is potential for corruption when officials take decisions that are potentially costly to private individuals or companies – e.g. tax incentives, zoning laws, timber rights and rights to extract mineral resources, investment permits, privatizations and monopoly rights over exports and imports or domestic activities (Abed and Davoodi, 2000; Tanzi, 1998). Factors that contribute indirectly to corruption include the quality and remuneration of the civil service, the effectiveness of deterrents, the example set by the country’s leadership, the nature of meritocratic recruitment and promotion in civil service, the quality and effectiveness of legal enforcement and the degree of transparency in government operations (Haque and Sahay, 1996; Van Rijckeghem and Weder, 1997). Poor governance can have a major negative impact on economic performance by reducing investment and economic growth. It diverts public resources toward private gains and away from needed public spending; it reduces public revenues, misallocates talent to rentseeking activities and distorts the composition of government expenditures and of tax revenues (Mauro, 1995). Empirical evidence suggests that corruption reduces spending on publicly provided social services (Tanzi and Davoodi, 1997) and results in lower spending on healthcare and education services, such as medicine and textbooks (Gupta, Davoodi and Tinogson, 2000). Higher levels of corruption also tend to be associated with rising military spending (Gupta, Mello and Saran, 2000). Corruption can worsen poverty and equity (see Section 2.3.5) because it exacerbates an unequal distribution of wealth and unequal access to education and other means to increase human capital (Gupta, Davoodi and Alonso-Terme, 1998; Hindriks, Keen and Muthoo, 1999). Given the high costs of corruption, why do governments not eliminate it? Because, when corruption is endemic, the likelihood of detection and punishment decreases and incentives are created for corruption to increase further. Individuals at the highest levels of government may have no incentives to control corruption or to refrain from taking part in rent-seeking activities. At the same time, eradication of corruption may be costlier in countries where the level of institutional development and the general economic environment is weak (DablaNorris and Freeman, 1999). Empirical evidence suggests that the rule of law (including effective anticorruption legislation), the availability of natural resources, the economy’s


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degree of competition and trade openness and the country’s industrial policy affect the breadth and scope of corruption (Leite and Weidmann, 1999).

1.2.2 Fulfilling major global agreements on sustainable development A second powerful motivation for developing the sustainomics framework is provided by the need to meet the many major global targets, relating to sustainable development, widely agreed by world leaders in recent years (see Section 1.3.1). The Stockholm Conference on the Human Environment in 1972 was a watershed gathering that brought the international community together to focus on development and environment issues. It focused on benefits of science and technology on economic growth. After 15 years, the report of the World Commission on Environment and Development (WCED, 1987) served as another important milestone, which brought the concept of sustainable development into the mainstream. The report succinctly paraphrased sustainable development, as ‘meeting the needs of the present generation without jeopardizing the ability of future generations to meet their needs’. However, due to lack of an operational definition and experience, little success was realized in practice. The next step was the Agenda 21 document agreed at the UN Earth Summit (UNCED) in Rio de Janeiro in 1992 (UN, 1992), which was intended as a blueprint for putting sustainable development into practice. Although the conference was able to generate worldwide enthusiasm, funding for the ambitious Agenda 21 targets never materialized. The UN Commission for Sustainable Development (CSD) was established to monitor progress on Agenda 21, but many indicators of sustainable development declined, particularly the environment indicators. Greater progress was made on other important agreements produced in Rio – e.g. the framework convention on climate change (UNFCCC) and the convention on biodiversity (CBD). Modest progress was also achieved after Rio with several new international agreements, including the Montreal Protocol (ozone), the Kyoto Protocol (climate) and the UN convention on desertification. In 2000, the UN Millennium Summit produced the Millennium Development Goals (MDGs), universally accepted by world leaders as a practical benchmark for measuring progress toward sustainable development (see Box 1.1 and Section 1.4). Supplementary targets were also agreed at the World Summit on Sustainable Development (WSSD) in Johannesburg in 2002. The WSSD focused on the shortcomings of the post-Rio development process, and sought to reinvigorate sustainable development activities worldwide. It yielded the goal-oriented and comprehensive Johannesburg Plan of Implementation, including targets relating to poverty and WEHAB (water, energy, health, agriculture and biodiversity). Most recently, in 2005 the UN Millennium Development Project was endorsed to press forward with the MDGs. In summary, there have been several international agreements on sustainable development during the past decades, but with progressively declining targets. At the same time, implementation of these goals has generally fallen short of their aims (see Section 1.4). Many international conferences and reports have helped to bring about a paradigm shift in development thinking. However, the linkages among scientific evidence,

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policy making and practical application need to be strengthened (see Section 1.3). In addition, scientific evidence and analysis are still inadequate on new global trends such as globalization and privatization, which implies that the achievement of MDG and WSSD targets will require dynamic implementation processes that adapt to new knowledge. Therefore, ongoing discussions and consensus-building among scientific experts, decision makers and other stakeholders need to be intensified.

1.2.3 Avoiding worst-case future scenarios and learning from past experience The third major motivation arises from the need to avoid disastrous future outcomes and learn the lessons of history relating to human development. Several ancient civilizations have shown remarkable durability by lasting 4000 years or more, including those located in the Yellow river basin in China, the Nile river basin in Egypt, and the Saraswati river basin in India. Other regions, such as the Sahel and the dust bowl in the USA, have demonstrated the fragility and collapse of carrying capacity in marginal lands exposed to the pressure of unsustainable human activity over time. Building on this historical experience and using modern analytical tools, a number of scenarios of future world development have emerged – see Table 1.1. While a range of optimistic and pessimistic futures are considered, we are especially concerned about avoiding the more disastrous scenarios. Among the undesirable and alarming outcomes are the ‘barbarization’scenario of the Global Scenarios Group, the IPCC A2 scenario projecting dangerously high growth of GHG emissions, and the Millennium Ecosystem Assessment ‘order from strength’ scenario. These scenarios provide ample motivation for renewed efforts to address the major global problems and prevent the potential deterioration of society into chaos and anarchy. One particular extrapolation of past experience serves as a powerful rationale for this book. Two catastrophic famines or holocausts during the late nineteenth century killed tens of millions in the developing world (Davis, 2001). They were the outcome of negative synergies between adverse global environmental factors (i.e. the El Niño droughts of 1876–1878 and 1898–1901) and the inadequate response of socioeconomic systems (i.e. vulnerability of tropical farming forcibly integrated into world commodity markets). In the eighteenth century, the quality of life in countries like Brazil, China and India was comparable with European standards. However, colonial dictates and rapid expansion of world trade reoriented production in developing countries (from food to cash crops) to service distant European markets. By the time the El Niño droughts struck in the nineteenth century, the domination of commodity and financial markets by Britain forced developing country small-holders to export cash crops at ever deteriorating terms of trade. This process undermined local food security, impoverished large populations and culminated in holocausts, on an unprecedented scale, which have been identified as one major cause of the present state of underdevelopment in the third world. From a sustainomics perspective, the corollary is clear, based on the precautionary principle (see Chapter 5). The future vulnerability of developing country food production systems to a combination of climate change impact and accelerated globalization of commodity and financial markets, poses significant risks to the survival of billions, especially in the poorest nations (Munasinghe, 2001a).


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Table 1.1 Summary of some recent global scenario exercises Name

Description

global scenarios based on three classes – conventional worlds, barbarization (bad), great transitions (good) (Gallopin, 1997; Raskin et al., 1998, 2002) Global Environment Outlook similar to GSG with emphasis on regional texture (UNEP, 2002) 3 (GEO-3) World Energy Council multiple global energy scenarios to year 2100 (Nakicenovic, Grubler (WEC) and McDonald, 1998) IPCC Emission Scenarios GHG emission scenarios to year 2100; axes of change are sustainable (SRES) versus unsustainable and globally integrated versus fragmented (IPCC, 2000) Millennium Ecosystem four scenarios based on future status of ecosystems (2003); axes of Assessment (MA) change are globally integrated versus regional and environmentally proactive versus reactive Global Scenario Group (GSG)

1.2.4 Vision for a practical way forward The fourth and final motivation is to set down some ideas which might serve as the first steps along a practical path toward the ultimate goal of sustainable development. This transition is depicted in Figure 1.1. (1) The top row shows that the extrapolation of current trends driven by forces like globalization and conventional market-oriented policies based on the so-called ‘Washington Consensus’ will pose significant risks. While policy reforms are proposed to correct for market deficiencies, issues arising from both the immediate drivers and underlying pressures are not being addressed systematically within a framework aimed at long-term sustainability (see Section 3.7). The main current policies tend to be reactive and defensive. Poverty, inequity, exclusion, conflict, poor governance and environmental damage could worsen sharply under such a business-as-usual approach and lead to a breakdown of global society. (2) The middle row depicts the practical contribution of the sustainomics approach. It offers an intermediate, but practical, step which takes us forward via proactive measures that make current development more sustainable. Society moves gradually toward the ultimate goal of sustainable development by influencing key immediate drivers of change, including consumption patterns, population, technology and governance – and thereby shaping global trends and managing market forces. Some aspects of the sustainomics framework also facilitate direct manipulation of underlying pressures. There is emphasis on early action to overcome the huge inertia of ‘supertanker Earth’, to begin steering it away from its risky current path toward safer waters using existing experience and tools. Co-evolving socioeconomic and ecological systems need to be guided by rational human foresight, at a moment in history where a major global transition might lead to disastrous results (see Section 4.1.3). (3) The bottom row indicates the long-term goal of making the transition to a new global sustainable development paradigm and sustainable lifestyle. Proponents seek deep changes, via a networked, multistakeholder, multilevel global citizens’ movement, responsive governance structure,

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Framework and fundamentals Main issues poverty, inequity, exclusion, conflict, environmental harm, etc.

Human interventions business-as-usual risks from unrestrained market forces at work (‘Washington consensus’, globalization, etc.)

Immediate drivers

consumption patterns, population, technology, governance

Intermediate practical step making development more sustainable (MDMS), using existing knowledge and lessons learned to manage market forces (sustainomics)

Underlying pressures

basic needs, social power structure, values, choices, knowledge base

Long-term goal fundamental global sustainable development transition through multilevel, multistakeholder, citizens’ networks, advanced policy tools, responsive governance and better technologies (new sustainable development paradigm)

Figure 1.1. Role of sustainomics in the long-term transition to global sustainable development.

improved policy tools, advanced technologies and better communications (including the Internet), which will work on underlying pressures linked to basic needs, social power structure, values, choices and knowledge base. The World Social Forum (Leite, 2005) and the Global Transition Initiative (Raskin, 2006) are two such efforts to build pluralistic global citizens’ networks. Chapter 6 describes some multilevel, multistakeholder, transdisciplinary dialogues, where networks of experts and practitioners play a key role.

1.3 Brief history and summary of sustainomics 1.3.1 Evolution of the sustainomics approach This section provides a brief overview, from an institutional perspective, of how sustainomics evolved. The Preface provides a more personal viewpoint. The sustainomics framework draws together two broad streams of thought – i.e. development (focused on human well-being) and sustainability (systems-science-oriented), as described below. Development stream (focused on human well-being) Current approaches to sustainable development draw on the experience of several decades of development efforts. Historically, the development of the industrialized world focused on material production as the basis of human well-being. Not surprisingly, most industrialized and developing nations have pursued the economic goal of increasing output and growth during the twentieth century. While the traditional approach to development was strongly associated with economic growth, it had important social dimensions as well. By the early 1960s, the large and growing numbers of poor in the developing world, and the lack of ‘trickle-down’ benefits to them, resulted in greater efforts to improve income distribution directly. The development paradigm shifted toward equitable growth,


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where social (distributional) objectives, especially poverty alleviation, were recognized as being distinct from, and as important as, economic efficiency in contributing to wellbeing. Protection of the environment has now become the third major objective of sustainable development. By the early 1980s, a large body of evidence had accumulated that environmental degradation was a major barrier to human development and well-being, and new proactive safeguards were introduced (such as the environmental assessments). Some key milestones relating to the evolution of recent thinking on sustainable development include: the 1972 United Nations Environmental Summit in Stockholm, the 1987 Bruntland Commission report, the 1992 United Nations Conference on Environment and Development (UNCED) in Rio de Janeiro, the 1995 World Summit on Social Development in Copenhagen, the UN Millennium Summit and Millennium Development Goals (MDGs) in 2000, the 2002 World Summit on Sustainable Development (WSSD) in Johannesburg, the UN Millennium Development Project approved as a follow-up to the MDGs in 2005 and the UN Decade on Education on Sustainable Development (1995– 2014); see Section 1.2.2. Sustainability stream (systems-science-oriented) Meanwhile, the scientific community became more interested in exploring the concept of sustainability. During the 1980s a number of relevant international scientific research initiatives dealing with nature emerged, including the World Climate Research Programme (WCRP) in 1980, the International Geosphere and Biosphere Programme (IGBP) in 1986 and DIVERSITAS (on biodiversity and ecology) in 1990. The United Nations Intergovernmental Panel on Climate Change (IPCC) was also established in 1988 (by WMO and UNEP), with global scientific expertise to assess periodically information on climate change. However, global sustainability issues like climate change were mainly framed by natural scientists as problems involving bio-geophysical systems, largely divorced from their social context. Although the social aspects have received increasing attention in the scientific debate, it was considered an ‘add-on’ rather than a fundamental element. In the 1990s, it was recognized that human activity was a major factor influencing global changes – e.g. in the work of existing scientific bodies such as the IPCC (Bruce, Lee and Haites, 1996; IPCC, 2001a) and in the creation of new bodies such as the International Human Dimensions to Global Environmental Change (IHDP) in 1996. In 1995, the IGBP GAIM (Global Analysis, Integration and Modelling) Task Force was established to integrate the knowledge generated in the various IGBP core projects. Since then, a series of international conferences and initiatives have called for (i) a more integrated approach between the natural and the social sciences and (ii) a better link between scientific activities and sustainable development problems – especially the human dimension. Among the significant outcomes of this trend was the Millennium Ecosystem Assessment (MA) launched by UN Secretary General Kofi Annan in 2001, which linked ecosystems, human communities and development.

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Emergence of sustainomics Amongst these multiple initiatives, the first ideas about sustainomics were outlined from 1990 onwards in several conference presentations by Mohan Munasinghe, culminating in a formal paper presented at the Rio Earth Summit in 1992, which set out key elements of the framework (Munasinghe, 1992a). These ideas were further elaborated for practical application (Munasinghe, 1994a). The aim was a more holistic and practical synthesis that would help to make development more sustainable by integrating the concerns of the development community (who focused on pressing development issues such as poverty, equity, hunger, employment, etc.) and the interests of the scientific community (who emphasized research on sustainability science, environment, etc.). The neologism ‘sustainomics’ was coined to project a more neutral image by focusing attention on sustainable development, so avoiding any disciplinary bias or hegemony. Sustainomics also seeks to balance people-oriented Southern Hemisphere priorities, including promotion of development, consumption and growth, poverty alleviation and equity, with environment-oriented Northern Hemisphere concerns about issues like natural resource depletion, pollution, the unsustainability of growth and population increase. Sustainable development is broadly described as ‘a process for improving the range of opportunities that will enable individual human beings and communities to achieve their aspirations and full potential over a sustained period of time, while maintaining the resilience of economic, social and environmental systems’ (Munasinghe, 1992a). Adapting this general concept, a more focused and practical approach toward making development more sustainable sought ‘continuing improvements in the present quality of life at a lower intensity of resource use, thereby leaving behind for future generations an undiminished stock of productive assets (i.e. manufactured, natural and social capital) that will enhance opportunities for improving their quality of life’. The sustainomics framework is described in greater detail in Chapter 2. In particular, it encourages decision making based on the balanced and consistent treatment of the economic, social and environmental dimensions of sustainable development, and draws on a sound but evolving body of scientific knowledge, including the natural and social sciences, engineering and humanities. A decade or more of experience in further developing and practically applying the sustainomics framework in the field was described at the 2002 World Summit on Sustainable Development (GOSL, 2002; Munasinghe, 2002a). Meanwhile, the approach has been cited and used in the work of many world bodies (e.g. ADB, CSD, EC, OECD, UNDP, UNEP, World Bank, etc.), governments (e.g. Canada, Netherlands, Philippines, Sri Lanka, UK, etc.) and individual researchers – specific references are given throughout the text. This book seeks to provide a comprehensive assessment of sustainomics today.

1.3.2 Summary of basic principles and methods The sustainomics framework draws on the following basic principles and methods (Munasinghe, 1992a, 1994a, 2002a); details are given in Chapter 2.


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(a) Making development more sustainable The step-by-step approach of ‘making development more sustainable’ (MDMS) becomes the prime objective, while sustainable development is defined as a process (rather than an end point). Since the precise definition of sustainable development remains an elusive, and perhaps unreachable, goal, a less ambitious strategy that merely seeks to make development more sustainable does offer greater promise. Such a gradient-based method is more practical and permits us to address urgent priorities without delay, because many unsustainable activities are easier to recognize and eliminate. Although MDMS is incremental, it does not imply any limitation in scope (e.g. restricted time horizon or geographic area – see (c) below). MDMS also seeks to keep future options open and identify robust strategies which meet multiple contingencies and increase resilience. Thus, while implementing short- and medium-term measures, we also follow a parallel track by continuing efforts to define and achieve the long-term goal of sustainable development. (b) Sustainable development triangle and balanced viewpoint Sustainable development requires balanced and integrated analysis from three main perspectives: social, economic and environmental. Each view corresponds to a domain (and system) that has its own distinct driving forces and objectives. The economy is geared toward improving human welfare, primarily through increases in the consumption of goods and services. The environmental domain focuses on protection of the integrity and resilience of ecological systems. The social domain emphasizes the enrichment of human relationships and the achievement of individual and group aspirations. Interactions among domains are also important. (c) Transcending conventional boundaries for better integration The analysis transcends conventional boundaries imposed by discipline, space, time, stakeholder viewpoints and operationality. The scope is broadened and extended in all domains to ensure a comprehensive view. Transdisciplinary analysis must cover economics, social science and ecology, as well as many other disciplines. Spatial analysis must range from the global to the very local, while the time horizon may extend to decades or centuries. Participation of all stakeholders (including government, private sector and civil society), through inclusion, empowerment and consultation, is important. The analysis needs to encompass the full operational cycle from data gathering to practical policy implementation and monitoring of outcomes. (d) Full-cycle application of practical and innovative analytical tools A variety of practical and novel analytical tools facilitate governance over the full cycle from initial data gathering to ultimate policy implementation and feedback. Two complementary approaches based on ‘optimality’ and ‘durability’ may be used to integrate and synthesize across economic, social and environmental domains, within an integrated assessment modelling framework. An issues-implementation transformation map

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(IITM) helps to translate issues in the environmental and social domains into the conventional national economic planning and implementing mechanisms within line ministries and departments. Restructuring the pattern of development to make economic growth more sustainable is explained through a ‘policy-tunnelling’ model, especially useful in poor countries, where poverty alleviation will require continued increases in income and consumption. Other practical tools include the Action Impact Matrix (AIM), integrated national economic– environmental accounting (SEEA), sustainable development assessment (SDA), environmental valuation, extended cost–benefit analysis (CBA), multicriteria analysis (MCA), integrated assessment models (IAMs) and so on. A range of sustainable development indicators help to measure progress and make choices at various levels of aggregation. The AIM process is the key link from initial data gathering to practical policy application and feedback. Critical sustainable development concerns are included in conventional national development strategy and goals in two main ways: an upward link, where sustainable development issues are embedded in the macrostrategy of a country via the medium- to long-term development path; and a downward link, where such issues are integrated into the national development strategy in the short- to medium-term, by carrying out SDAs of microlevel projects and policies. Brief review of key ideas The principle conclusion of this book is that we have made significant progress toward understanding and implementing the concept of sustainable development since the 1990s. The way forward is by taking practical steps toward MDMS, as set out in the sustainomics framework. Many unsustainable practices are obvious and may be addressed incrementally today, as we progress toward the long-term (and less clear) goal of sustainable development. Sufficient examples exist of good (and bad) practices, and the lessons learned permit us to address immediate problems such as poverty, hunger and environmental degradation in a more sustainable manner, while concurrently seeking to define better and attain the ultimate goal of sustainable development. The core principles underlying the sustainomics framework provide a good starting point for systematic analysis of sustainable development problems: (a) making development more sustainable; (b) sustainable development triangle (economic, social and environmental dimensions) and balanced viewpoint; (c) transcending conventional boundaries (discipline, space, time, stakeholder viewpoint and operationality) for better integration; and (d) fullcycle application of practical and innovative analytical tools (including the AIM). Furthermore, the case studies in this book (and elsewhere) demonstrate that the approach of making development more sustainable has already yielded encouraging practical results and shows increasing promise for the future. Specific examples described here begin with global problems such as climate change and the analysis of international- and national-level policy responses. Next, we learn from the experience of transnational institutions like the World Commission on Dams (WCD), the Intergovernmental Panel on Climate Change (IPCC), the Millennium Ecosystems Assessment (MA) and the Millennium Development


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Goals (MDGs), which work through multistakeholder, multilevel, multidisciplinary processes involving governments, business, civil society and scientists. At the national macroeconomic level, a wide range of country applications involving a variety of models are presented, which provide useful insights for practical economy-wide policies. Within countries, case studies cover sustainable development of key sectors like energy, transport and water, as well as important ecological systems involving forests and agriculture. Resource pricing policy could be used as a practical and flexible tool for making development more sustainable. Finally, the book shows how the sustainomics framework may be applied at the project and local levels, in areas such as hydropower, solar energy, water supply, sustainable hazard reduction and disaster management and urban growth. We accept that sustainomics is incomplete – there are both gaps in knowledge and problems of implementation. Nevertheless, our hope and expectation is that the important contributions of other potential ‘sustainomists’ will rapidly help to further flesh out the initial framework and applications set out in this volume. 1.4 Millennium development prospects and worldwide status This section reviews recent trends and prospects in relation to the MDGs as an appropriate backdrop for the subsequent chapters. One yardstick for measuring the progress of civilization is the ability of humans to manipulate energy, matter and information. We may distinguish four eras (De Vries and Goudsblom, 2002; Munasinghe, 1987, 1989). The first was the nomadic hunter–gatherer phase starting several million years ago, including the domestication of fire and use of stone tools. Around 8000 BC a second transition to the agricultural period began, associated with farming settlements and agricultural implements. The advent of the industrial age in the eighteenth century was even more rapid, and was characterized by increasingly crowded and polluted urban centres and machines. The twentieth century marks the fourth transition to a planetary civilization, increasingly linked together by fast communications, rapid transportation, information technology and computers. During this process, both extensive and intensive development took place. With each transition, extensive development and growth in the scale of activities expanded the footprint of humanity (see Figure 2.8). At the same time, intensive development increased the internal complexity, interlinkages and ability to process information within society. Nevertheless, human beings are still utterly dependent on the bio-geosphere for their existence and, thus, extensive growth makes us more vulnerable to environmental degradation. Meanwhile, intensive development improves resilience due to greater complexity, interconnections and redundancy, but also increases vulnerability to harmful disturbances that are quickly transmitted to all parts of the globe (e.g. financial and market instabilities or new diseases). Many recent books have set out key sustainable development problems and potential remedies – taking optimistic, pessimistic or intermediate viewpoints (Easterbrook, 1995; Environment and Development Economics, 1998; IPCC, 2001a; Jodha, 2001; Lomborg, 2001; MA, 2005a; Maddison, 2001; McNeill, 2000; MDG, 2005; Munasinghe and Swart,

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2005; Myers and Simon, 1994; Speth, 2004; UNDP, 2005b; World Bank, 2006; Worldwatch, 2003). While it is difficult to generalize, environmentalists and natural scientists have tended to see the glass half empty, while economists and technological optimists have perceived the glass half full – reflecting a range of opinions. This book takes the middle path, arguing that the problems are serious enough to warrant urgent attention, while noting that existing and emerging remedies could provide adequate solutions if early action is taken. Below, we summarize the disappointing progress on the MDGs – the most widely accepted set of global sustainable development targets today.

Poverty and hunger More than 1 billion people survive on less than $1 a day. More than 800 million people have too little to eat to meet their daily energy needs. Over 25% of children under the age of five in developing countries are malnourished, retarding their physical and mental development and threatening their survival. In Asia, the number of people living on less than $1 a day dropped by nearly a quarter of a billion from 1990 to 2001. In over 30 countries, hunger was reduced by at least 25% during the last decade. Sub-Saharan Africa is the hardest hit by hunger and malnutrition. The proportion of people lacking the food needed to meet their daily needs is on the decline (see Section 13.3). The percentage of people with insufficient food was lower in 2000–2002 than in 1990–1992 in all regions except Western Asia. However, progress has slowed, and the number of hungry people increased between 1997 and 2002, probably due to growing populations and poor agricultural productivity. Hunger tends to be concentrated among the landless or among farmers whose plots are too small to provide for their needs. Efforts to eradicate poverty and hunger are frequently set back by conflict and natural disasters. The average income of the extremely poor in Sub-Saharan Africa has declined. Reversing this negative trend requires faster economic growth that reaches the poor – a challenging task in the face of disease and armed conflicts. Hunger and poverty, in turn, can provide fertile ground for conflict (especially when combined with factors such as inequality) and make it more difficult to cope with disasters. Strategies to combat child malnutrition include breastfeeding for the first six months, increasing the use of micronutrient supplements, reducing infectious diseases and improving access to clean water and sanitation. Primary education More than 115 million children of primary school age do not go through proper schooling. These are mostly children from poor households, whose mothers often have no formal education either. Education, especially for girls, has social and economic benefits for society as a whole. Achieving this goal will require dramatically scaled-up efforts in Sub-Saharan


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Africa, Southern Asia and Oceania. In these regions and elsewhere, increased enrolment must be accompanied by efforts to ensure that all children remain in school and receive a high-quality education. In five regions, 90% of children or more are enrolled in primary school. Sub-Saharan Africa has made progress, but still has over one-third of its children out of school. In Southern Asia, Oceania and Western Asia, enrolment is also lagging, with about 20% of children out of school. Gender equality Achieving parity in education is critical if women are to engage fully in society and the global economy. Although women have increased their share in paid non-agricultural employment, they remain a small minority in salaried jobs and are overrepresented in the informal economy. Having an equal voice in decisions is a key element of women’s empowerment. Countries with the widest gender gap in primary education have made progress in increasing the proportion of girls enrolled in school. This gap still remains a serious concern in Southern Asia, Sub-Saharan Africa and Western Asia. In countries where resources and school facilities are lacking, only boys are sent to school. However, in countries where overall enrolments are high, girls are well represented in both primary and secondary education (e.g. in Latin America). Women’s access to paid employment is lower than men’s in most of the developing world. Women in Southern Asia, Western Asia and Northern Africa still hold only about 20% of paying jobs in sectors outside of agriculture. In Latin America and the Caribbean, women now hold over 40% of paying jobs. Over 60% of people working in family enterprises without pay are women. Child mortality Every year, almost 11 million children below the age of five die (about 30 000 children a day). Most live in developing countries and die from a disease or a combination of diseases that can be prevented or treated by existing inexpensive means. Malnutrition contributes to over half these deaths. Improvements in public-health services are key, including safe water and better sanitation. Education, especially for girls and mothers, saves children’s lives. Raising incomes can help, but little will be achieved unless services reach those who need them most. In 1960, more than one child in five died before the age of five in the developing regions. By 1990, the rate decreased to one in ten. Only in Northern Africa, Latin America and the Caribbean and South-Eastern Asia has this pace been maintained. In these regions, economic growth, better nutrition and access to healthcare have spurred improvements in child survival. Almost half of all deaths among children under five occur in Sub-Saharan Africa, where progress has slowed owing to weak health systems, conflicts and AIDS. More than one-third of all deaths occur in Southern Asia, despite the reduction in poverty. Countries that have experienced conflict, including Cambodia and Iraq, have seen sharp increases or

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no improvement in child mortality since 1990. Countries reeling from AIDS, especially in Southern Africa, have also seen an increase in child mortality. Most of these lives could be saved by expanding low-cost prevention and treatment measures. These include exclusive breastfeeding of infants, antibiotics for acute respiratory infections, oral rehydration for diarrhoea, immunization and the use of insecticide-treated mosquito nets and appropriate drugs for malaria. Proper nutrition is part of prevention, because malnutrition increases the risk of dying from these diseases. Better care for mothers and babies before and after birth would reduce the one-third of these deaths that occur in the first days of life. Maternal health Currently, 200 million women have an unmet need for safe and effective contraceptive services; 20 times as many women suffer serious injuries or disabilities. Countries with already low levels of maternal mortality have made progress. Reductions in the worstaffected countries will require additional resources to ensure that the majority of births are attended by doctors, nurses or midwives who are able to prevent, detect and manage obstetric complications. When problems do arise, women must be able to reach a fully equipped medical facility in time. Universal access to reproductive healthcare, including family planning, is the starting point for maternal health. In 2000, the average risk of dying during pregnancy or childbirth in the developing world was 450 per 100 000 live births. The chances of dying during pregnancy or childbirth over a lifetime are as high as one in 16 in Sub-Saharan Africa, compared with one in 3800 in the developed world. This risk could be substantially reduced if women had adequate family planning services, good medical care and access to emergency obstetric-care facilities in case of unexpected complications. Advances were made in most developing regions between 1990 and 2003 in providing medically skilled attendants at birth. Major improvements were achieved in South-Eastern Asia, Northern Africa and Eastern Asia, but there was no change in Sub-Saharan Africa, where maternal mortality is highest. HIV/AIDs, malaria and other diseases More than 20 million people have died around the world since the epidemic began (in the 1980s), it being the leading cause of premature death in Sub-Saharan Africa and the fourth largest killer worldwide; by the end of 2004, an estimated 39 million people were living with HIV. Thailand and Uganda have shown that infection rates can be reversed with vision and leadership. Historically, malaria has been a far greater scourge. It currently claims the lives of a million people a year and is estimated to have slowed economic growth in African countries by 1.3% a year. Tuberculosis, once thought defeated, is making a comeback, helped by the emergence of drug-resistant strains and the vulnerabilities created by HIV and AIDS. Not surprisingly, all three of these diseases are concentrated in the poorest countries. They can be largely controlled through education, prevention, treatment and care.


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Globally, 4.9 million people were newly infected with HIV in 2004 and 3.1 million died. HIV is spreading fastest in the European countries of CIS and in parts of Asia. In countries where the epidemic is still at an early stage, programmes targeted at the most vulnerable are effective. Because there is no cure for AIDS, prevention is essential. But millions of young people know too little about HIV to protect themselves. Surveys in Sub-Saharan Africa and SouthEastern Asia show low knowledge about the basics about how to avoid infection. During the second half of 2004, the number of people receiving antiretroviral therapy in developing regions increased from 440 000 to 700 000, but that figure is only about 12% of those who would benefit from these medications. Treatment and care need to be expanded to reach millions more. Malaria is endemic in many of the world’s poorest countries, affecting 350–500 million people a year; 90% of the one million malaria deaths each year occur in Sub-Saharan Africa, where more than 2000 children die each day from malaria. Tuberculosis kills 1.7 million people a year, most of them in their prime productive years. The number of new tuberculosis cases has been growing by about 1% a year, with the fastest increases in Sub-Saharan Africa and CIS. In 2003, there were nearly 9 million new cases, including 674 000 among people living with HIV. Environmental sustainability Land is becoming degraded at an alarming rate. Plant and animal species are being lost in record numbers. The climate is changing, bringing with it threats of rising sea levels and worsening droughts and floods. Fisheries and other marine resources are being overexploited. The rural poor are most immediately affected because their day-to-day subsistence and livelihoods more often depend on the natural resources around them. Though the exodus to urban areas has reduced pressure on rural lands, it has increased the number of people living in unsafe and overcrowded urban slums. In both urban and rural areas, billions of people lack safe drinking water and basic sanitation. Overcoming these and other environmental problems will require greater attention to the plight of the poor and an unprecedented level of global cooperation. Forests cover one-third of the Earth’s surface and constitute one of the richest ecosystems. In the last decade alone, 940 000 square kilometres of forest were converted into farmland, logged or lost to other uses. Some 19 million square kilometres (over 13% of the Earth’s land surface) have been designated as protected areas. This represents an increase of 15% since 1994. Loss of habitats and biological diversity continues, with more than 10 000 species considered to be under threat. The transfer of new energy-efficient technologies to developing countries is not happening fast enough. In poor nations, the lack of clean fuels has a direct impact on rural households, which depend on wood, dung, crop residues and charcoal for cooking and heating. Indoor air pollution caused by these fuels is estimated to cause more than 1.6 million deaths per year, mostly among women and children. The fraction of population using safe sources of drinking water in the developing world increased from 71% in 1990 to 79% in 2002. However, over 1 billion people have yet to

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benefit, with lowest coverage in rural areas and urban slums. In Sub-Saharan Africa, 42% of the population is still unserved. The obstacles to progress (which include conflict, political instability and low priority for investments in water and sanitation) are especially daunting because of high-population-growth rates. Much slower progress has been made globally in improving sanitation. About 2.6 billion people (representing half the developing world) lack toilets and other forms of improved sanitation. Sanitation coverage in the developing world rose from 34% in 1990 to 49% in 2002. If present trends continue, close to 2.4 billion people worldwide will still be without improved sanitation in 2015. A dramatic increase in investment is needed to meet the sanitation target. The urban population of developing countries is growing at over 3% per year, or three times faster than in rural areas. Thus, including migration to the cities and additional births, about 100 million people are added to urban communities of the developing world each year. By 2008, the urban population will exceed the rural population in developing regions. Nearly one in three city dwellers (almost one billion people) live in slums, in conditions characterized by overcrowding, few jobs or security of tenure, poor water, sanitation and health services and widespread insecurity, including violence against women. Not surprisingly, disease, mortality and malnutrition are much higher in slums than in planned urban areas. Surveys suggest that in some African cities the death rate of children under five who live in slums is about twice as high as that of children in other urban communities.

2 Sustainomics framework1

In this chapter, the elements of the sustainomics framework are set out in greater detail. Section 2.1 describes the fundamental principles and methods. Sustainable development, traditional development and growth are defined. A practical approach based on making development more sustainable, or MDMS, is described as an alternative to pursuing abstract definitions of sustainable development. The sustainable development triangle (comprising social, economic and environmental dimensions) is introduced, and the driving forces and concepts of sustainability underlying each viewpoint are explained. Sustainomics also promotes methods which transcend conventional boundaries of thinking and full-cycle analysis from data gathering to practical policy implementation. In Section 2.2, the dimensions of the sustainable development triangle, their interactions and different concepts of sustainability are explained. Methods for integrating these three dimensions are described in Section 2.3, including the complementary concepts of optimality and durability. The poverty–equity–population–natural-resources nexus, and linkages between economic efficiency and social equity, are discussed. Section 2.4 describes a variety of practical methods and tools for applying sustainomics principles to the real world, including the Action Impact Matrix, sustainable development assessment, cost–benefit analysis, multicriteria analysis and so on. It is important to select relevant time- and location-specific indicators of sustainable development. Section 2.5 outlines approaches for restructuring long-term growth and development to make them more sustainable by harmonizing development with nature, while pursuing poverty reduction in developing countries that require continued growth of incomes and consumption.

2.1 Basic concepts and principles World decision makers are facing traditional development issues (such as economic stagnation, persistent poverty, hunger and illness) as well as new challenges (like environmental damage and globalization). One key approach that has emerged is the concept of sustainable development or ‘development which lasts’. Following the 1992 Earth Summit in Rio de Janeiro and the adoption of the United Nations Agenda 21, this idea has become well 1

Some parts of the chapter are based on material adapted from Munasinghe (1992a, 1994a, 2002a, 2004a).

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accepted worldwide (UN, 1992; WCED, 1987). Subsequently, international events like the 2000 Millennium Development Goals (MDGs) and the 2002 World Summit on Sustainable Development (WSSD) in Johannesburg have helped to maintain the impetus. The Bruntland Commission’s original definition of sustainable development was succinctly paraphrased as ‘meeting the needs of the present generation without jeopardizing the ability of future generations to meet their needs’ (WCED, 1987). As a contribution to define, analyse and implement sustainable development better, Munasinghe (1992a, 1994a) proposed the term sustainomics to describe ‘a transdisciplinary, integrative, comprehensive, balanced, heuristic and practical framework for making development more sustainable’. Many other definitions have been proposed, but it is not the purpose of this book to review them. Sustainomics broadly describes sustainable development as ‘A process for improving the range of opportunities that will enable individual human beings and communities to achieve their aspirations and full potential over a sustained period of time, while maintaining the resilience of economic, social and environmental systems.’ This definition recognizes that the development of economic, social and ecological systems depends on expanding the set of opportunities for their improvement. Meanwhile, the sustainability of systems will be enhanced by improving their resilience and adaptive capacity. Based on this approach, a more focused and practical approach toward making development more sustainable also emerged, which sought ‘continuing improvements in the present quality of life at a lower intensity of resource use, thereby leaving behind for future generations an undiminished stock of productive assets (i.e. manufactured, natural and social capital) that will enhance opportunities for improving their quality of life’ (Munasinghe, 1992a). This evolution of ideas takes us beyond traditional ‘development’ (which relates to improving broadly the well-being of individuals and communities) and growth (which refers to increases in economic output or value added in goods and services, conventionally measured by gross national product, etc.). The heuristic element in sustainomics underlines the need for continuous adaptation and rethinking of the framework based on new research, empirical findings and current best practice, because reality is more complex than our incomplete models. The current state of knowledge is inadequate and does not provide a comprehensive definition of sustainomics. Sustainomics must provide a dynamically evolving learning framework to address rapidly changing sustainable development issues. The basic ideas about sustainomics sketched out below have benefited greatly from the post-Bruntland discussions and the work of other researchers. They also provide a fresh start. The intent is to stimulate discussion and further research that will help to flesh out further the basic framework. Many authors (cited throughout the text) have already contributed significantly to this effort with work that is related to the sustainomics approach and the sustainable development triangle. The core framework rests on several basic principles and methods: (a) making development more sustainable (MDMS); (b) the sustainable development triangle and balanced treatment;

2 Sustainomics framework

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(c) transcending conventional boundaries for better integration; and (d) full-cycle application of practical analytical tools and methods, from data gathering to policy implementation and operational feedback.

2.1.1 Making development more sustainable Since the precise definition of sustainable development remains an elusive goal, a less ambitious strategy might offer greater promise. Thus, the step-by-step approach of ‘making development more sustainable’ (MDMS) becomes the prime objective, while sustainable development is defined as a process rather than an end point (see Section 2.2). Such an incremental (or gradient-based) method is more practical and permits us to address urgent priorities without delay, while avoiding lengthy philosophical debates about the precise definition of sustainable development. However, this approach does not eliminate the need to have a practical metric to measure progress toward sustainable development. MDMS suggests a pragmatic, systematic process. We start with the many unsustainable activities that are easiest to recognize and eliminate – for example, reducing land degradation through improved farming practices, or conserving energy by switching off unnecessary lights. Section 2.1.2 argues that an appropriate measurement framework should cover the economic, social and environmental dimensions of sustainable development. Especially critical is the choice of appropriate indicators to suit the application (see Section 2.4.2). Conventional economic evaluation attempts to measure all such indicators (economic, social and environmental) in monetary units and then use economic cost–benefit analysis criteria to test for viability (see Section 3.2). However, problems arise because cost–benefit analysis is based on the concept of optimality, which differs from sustainability (see Section 2.3), and such economic valuation is often difficult to do. In that case, our MDMS metric will need to rely on indicators that have different units of measurement (monetary, biophysical, social, etc.) and corresponding sustainability criteria. Multicriteria analysis is more suitable to assess indicators that cannot be directly compared (see Section 3.6). If an activity results in an improvement of all sustainability indicators, it clearly satisfies the MDMS requirement – also called a ‘win–win’ outcome. For other actions, some sustainability indicators may improve while others worsen. In such cases, judgement is required to trade-off one indicator against another, and practical ways of addressing such issues are discussed in the case studies (Chapters 5 to 16). This process needs to adapt continuously and improve itself, as scientific knowledge about sustainable development improves. Instead of criticising the shortcomings of other disciplines, sustainomics takes a positive and practical viewpoint by borrowing appropriate methods and tools. Reliance on an eclectic set of concepts and methods does not imply lack of rigour, but rather underlines the value of diversity in cross-disciplinary thinking. However, concepts drawn from different disciplines may not be mutually consistent, and thus require more efforts to ensure transdisciplinary integration (see Sections 2.1 to 2.2). Although MDMS is incremental, it does not imply any limitation in scope (e.g. restricted time horizon or geographic area; see Section 2.1.3). Thus, the effects of specific near-term

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actions on long-run sustainable development prospects need to be analysed within the sustainomics framework. While pursuing the MDMS approach to deal with current problems, we also follow a parallel track by seeking to define better the ultimate goal of sustainable development (see Section 1.3). In particular, it is important to avoid sudden catastrophic (‘cliff edge’) outcomes, in case our MDMS analysis is too restricted and ‘myopic’. Similarly, incremental analysis may fail to detect serious consequences of large-scale changes (see Section 2.5.1). Finally, MDMS encourages us to keep future options open and seek robust strategies that could meet multiple contingencies, thereby increasing resilience and durability (see Section 2.3).

2.1.2 Sustainable development triangle and balanced treatment Current thinking on the concept has evolved to encompass three major points of view: economic, social and environmental, as represented by the sustainable development triangle in Figure 2.1 (Munasinghe, 1992a). Each viewpoint corresponds to a domain (and system) that has its own distinct driving forces and objectives. The economy is geared mainly toward improving human welfare, primarily through increases in the consumption of goods and services. The environmental domain focuses on protection of the integrity and resilience of

poverty equity sustainability climate change

on ati liz na ts ter pac / in on f im ati e o alu nc • v cide • in

• in • b trag asi ene c n rat eed ion s / l al e ive qu lih ity oo ds

• growth • efficiency • stability Economic

• intergenerational equity Social • values /culture • empowerment • inclusion/consultation • institutions/governance

Environmental • resilience / biodiversity • natural resources • pollution

Figure 2.1. Sustainable development triangle – key elements and interconnections (corners, sides, centre).


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ecological systems. The social domain emphasizes the enrichment of human relationships and the achievement of individual and group aspirations. During the preparations for the 1992 Earth Summit in Rio de Janeiro, there was a lively debate on how the ‘three pillars’ (environment, economy and society) might be integrated within development policy. The sustainable development triangle was presented at Rio to emphasize that the sides and interior of the triangle (representing interaction among the three pillars) are as important as the three vertices – e.g. placing an issue like poverty or climate change in the centre reminds us that it should be analysed in all three dimensions (Munasinghe, 1992a). There was considerable resistance to the idea, mainly due to disciplinary rivalries. However, by the time of the 2002 World Summit on Sustainable Development (WSSD) in Johannesburg, the approach had become widely accepted (e.g. GOSL, 2002). Several versions of the triangle are in operational use today (e.g. Hinterberger and Luks, 2001; Odeh, 2005; World Bank, 1996a). For some specialized applications, a fourth vertex such as ‘institutions’ or ‘technology’ has been proposed, converting the triangle into a pyramid. While these additions are useful in specific cases, the original triangle retains its advantages of simplicity and versatility. Key features of the three vertices of the sustainable development triangle (economic, social and environmental) are elaborated upon in Section 2.2. The linkages represented by the sides of the triangle are explained in Section 2.3.5 and Box 2.4 (mainly social–economic, dealing with poverty and equity), Chapter 3 (economic–environmental) and Chapter 4 (environmental–social). Methods of integrating all three dimensions are introduced in Section 2.3. The case studies in Chapters 5 to 16 explore the three dimensions and their interactions – not always comprehensively or symmetrically, because the relative emphasis varies according to the circumstances and policy-relevance. These applications chapters are structured on a spatial scale, from global to local. The substantive transdisiplinary framework underlying sustainomics should lead to the balanced and consistent treatment of the economic, social and environmental dimensions of sustainable development (as well as other relevant disciplines and paradigms). Balance is also needed in the relative emphasis placed on traditional development versus sustainability. For example, Southern Hemisphere priorities include continuing development, consumption and growth, poverty alleviation and equity, whereas much of the mainstream literature on sustainable development which originates in the Northern Hemisphere tends to focus on pollution, the unsustainability of growth and population increase.

2.1.3 Transcending conventional boundaries for better integration Sustainable development encompasses all human activities, including complex interactions among socioeconomic, ecological and physical systems. Accordingly, sustainomics encourages practitioners to synthesize novel solutions by transcending conventional boundaries imposed by discipline, space, time, stakeholder viewpoint and operational focus.

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Discipline The neologism ‘sustainomics’ underlines the fact that the emphasis is explicitly on sustainable development, and emphasizes a neutral approach free of any disciplinary bias or hegemony. Several authors suggest that sustainomics represents a new discipline, paradigm or science (e.g. Markandya et al., 2002; Vanderstraetten, 2001). We stress that sustainomics is a practical, transdisciplinary framework (or ‘transdiscipline’) that seeks to establish an overarching, ‘holistic’ design for analysis and policy guidance, while the constituent components (principles, methods and tools drawn from many other disciplines) provide the rigorous ‘reductionist’ building blocks and foundation. It complements rather than replaces other approaches to addressing sustainable development issues. The multiplicity and complexity of issues involved cannot be covered fully by a single discipline. Hitherto, multidisciplinary teams, involving specialists from different disciplines, have been applied to sustainable development issues. Interdisciplinary work goes a step further by seeking to break down the barriers among various disciplines. However, what is now required is a truly transdisciplinary framework, which would bridge and weave the scientific knowledge from diverse disciplines into new concepts and methods, while facilitating a full information exchange among all stakeholders that could address the many facets of sustainable development – from concept to policy and actual practice (Box 2.1). Thus, sustainomics would provide a more comprehensive framework and eclectic knowledge base to make development more sustainable. The sustainomics approach seeks to integrate knowledge from both the sustainability and development domains (see Chapter 1). Thus, it draws on information from other recent initiatives such as ‘sustainability transition’ and ‘sustainability science’ (Parris and Kates, 2001; Tellus Institute, 2001). Such a synthesis needs to make use of core disciplines such as ecology, economics and sociology, as well as anthropology, botany, chemistry, demography, ethics, geography, law, philosophy, physics, psychology, zoology, etc. Technological skills such as engineering, biotechnology and information technology also play a key role. Spatial and temporal scales The scope of analysis needs to extend geographically from the global to the local scale, cover time spans extending to centuries (e.g. in the case of climate change) and deal with problems of uncertainty, irreversibility and non-linearity. Multiscale analysis (Box 2.2) and multistakeholder involvement are especially important with growing globalization of economic, social and environmental issues. The case studies in Chapters 5 to 16 are ordered on a spatial scale (global to local). Stakeholder viewpoints and operational focus Sustainomics encourages multistakeholder participation through inclusion, empowerment and consultation in analysis and decision making (see Chapter 6). Such processes not only help to build the consensus, but also promote ownership of outcomes and facilitate implementation of agreed policies. Three basic groups – government, civil society and the business community – need to collaborate to make development more sustainable at the


Box 2.1 Transdisciplinary methods Sustainomics is a neutral expression – the neologism focuses attention on sustainable development without any disciplinary bias. It has much in common with other transdisciplinary methods that attempt to bridge the economy–society–environment interfaces. Distinctive features of sustainomics include the focus on making development more sustainable, discipline neutrality, applications orientation and policy-relevance. It prefers to draw on other disciplines to use the most practical and appropriate methods available (with relevant caveats and cautions), rather than to criticize them. One closely related field is ecological economics, which combines ecological and economic methods to address a range of problems and emphasizes the importance of key concepts such as the scale of economic activities (Costanza et al., 1997). Environmental and resource economics attempts to incorporate environmental concerns into traditional neoclassical economic analysis (Freeman, 1993; Tietenberg, 1992). Newer areas related to ecological science, such as conservation ecology, ecosystem management, industrial ecology and political ecology, have birthed alternative approaches to the problems of sustainability, including crucial concepts such as system resilience and integrated analysis of ecosystems and human actors (Holling and Walker, 2003). Key papers in sociology have explored ideas about the integrative glue that binds societies together, while drawing attention to the concept of social capital and the importance of social inclusion (Grootaert, 1998; Putnam, 1993). The literature on systems, energetics and energy economics has focused on the relevance of physical laws such as the first and second laws of thermodynamics (covering mass/energy balance and entropy, respectively). This research has yielded valuable insights into how stocks and flows of energy, matter and information link physical, ecological and socioeconomic systems together, and has analysed the limits placed on ecological and socioeconomic processes by laws governing the transformation of ‘more available’ (low-entropy) to ‘less available’ (high-entropy) energy (Boulding, 1966; Georgescu-Roegen, 1971; Hall, 1995; Munasinghe, 1990a). Recent work on cultural economics, environmental psychology, economics of sociology, environmental sociology, social psychology, sociological economics and sociology of the environment are also relevant. The literature on environmental ethics has explored many issues, including the weights to be attached to values and human motivations, decision-making processes, consequences of decisions, intra- and intergenerational equity, the ‘rights’ of animals and the rest of nature and human responsibility for the stewardship of the environment (Andersen, 1993; Sen, 1987; Westra, 1994; see also various issues of the Elsevier journal Environmental Ethics). Understanding human behaviour is a challenge to all disciplines. For example, both biology and sociology can provide important insights into this problem that challenge the ‘rational actor’ assumptions of neoclassical economics (see Box 2.2). Thus, recent studies seek to explain phenomena such as hyperbolic discounting (versus the more conventional exponential discounting), reciprocity and altruistic responses (as opposed

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to selfish, individualistic behaviour) (Gintis, 2000; Robson, 2001). Siebhuner (2000) defines ‘homo sustinens’ as a moral, cooperative individual with social, emotional and nature-related skills, as opposed to the conventional ‘homo economicus’, who is motivated primarily by economic self-interest and competitive instincts. Neoclassical economics has been criticized both for ignoring fundamental physical limitations (Georgescu-Roegen, 1971) and for being mechanistically (and mistakenly) modelled on classical thermodynamics (Sousa and Domingo, 2006).

Box 2.2 Multiscale spatial and temporal aspects of sustainable systems An operationally useful concept of sustainability must refer to the persistence, viability and resilience of organic, biological and social systems, over their ‘normal’ lifespan (see Section 2.2.2). Sustainability is linked to both spatial and temporal scales, as shown in Figure B2.1. The x-axis indicates lifetime in years and the y-axis shows linear size (both in logarithmic scale). The central circle represents an individual human being – having a longevity and size of the order of 100 years and 1.5 metres, respectively. The

scale (metres)

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planetary ecosystem

106

society/large ecosystem

103

local population group

1

unsustainable systems (premature death/collapse)

forecasting limit

organism human brittle systems (unable to adapt/evolve)

10–3 cell 10–6

10–2

1

102 time (years)

Figure B2.1. Transcending spatial and temporal scales.

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106

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diagonal band shows the expected or ‘normal’ range of lifespans for a nested hierarchy of living systems (both ecological and social), starting with single cells and culminating in the planetary ecosystem. The bandwidth accommodates the variability in organisms and systems, as well as longevity. We may argue that sustainability requires living systems to be able to enjoy a normal lifespan and function normally within the range indicated in the figure. Environmental changes that reduce the lifespan below the normal range imply that external conditions have made the system unsustainable. For example, the horizontal arrow might represent an infant death – indicating an unacceptable deterioration in human health and living conditions. Thus, the regime above and to the left of the normal range denotes premature death or collapse. At the same time, no system is expected to last forever. Indeed, each sub-system of a larger system (such as single cells within a multicellular organism) generally has a shorter lifespan than the larger system itself. If sub-system lifespans increase too much, the system above it is likely to lose its plasticity and become ‘brittle’ – as indicated by the region below and to the right of the normal range (Holling, 1973). Gunderson and Holling (2001) use the term ‘panarchy’ to denote such a nested hierarchy of systems and their adaptive cycles across scales (see Section 4.1.3). Forecasting over a timescale of several hundred years is rather imprecise. Thus, it is important to improve the accuracy of scientific analysis to make very long-term predictions about sustainability more convincing – especially in the context of persuading decision makers to spend large sums of money to reduce unsustainability. The precautionary approach is one way of dealing with uncertainty, especially if potential risks are large – i.e. avoiding unsustainable behaviour using low-cost measures, while studying the issue more carefully.

local, national and global levels. This multistakeholder, multilevel breakdown may be further tailored to suit location-specific circumstances (see Chapter 6). The principle of subsidiarity is especially important for good governance, whereby decentralized decisions are taken and implemented at the lowest practical and effective level. The analytical process is operationally focused. The full cycle includes purposeful data gathering and observations, concepts and ideas, issues, models and analysis, results, remedies, policies and plans, implementation, monitoring, review and feedback.

2.1.4 Full-cycle application of practical analytical tools Sustainomics includes a set of analytical tools that facilitate practical solutions to real-world problems over the full operational cycle, from data gathering to policy implementation. These elements are described below, including optimality and durability, issues–policy mapping, policy tunnelling, the Action Impact Matrix, sustainable development assessment, environmental valuation, extended cost–benefit analysis, multicriteria analysis, etc. Practical applications and case studies are provided in Chapters 5 to 16.

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2.2 Key elements of the sustainable development triangle Chapter 1 described the past evolution of economic, social and environmental thinking within the development paradigm. We elaborate on current ideas in this area and the need for an integrated approach.

2.2.1 Economic aspects Economic progress is evaluated in terms of welfare (or utility) – measured as willingness-topay for goods and services consumed. Thus, economic policies typically seek to increase conventional gross national product (GNP) and induce more efficient production and consumption of (mainly marketed) goods and services. The stability of prices and employment are among other important objectives. At the macrolevel, some researchers have highlighted the role of economic forces such as world trade to explain differences in affluence and growth rates of nations (Frankel and Romer, 1999; World Bank, 1993d). Mainstream (neoclassical) economics provides the concepts underlying this framework (Box 2.2). However, human well-being also depends on bodily and mental health status. Often, economic, physical and psychological aspects of well-being support each other. For example, good physical health enhances income-earning capacity and psychological satisfaction. Most religions emphasize non-material aspects. Typically, Buddhist philosophy (over 2500 years old) classified a comprehensive list of human desires and stressed that contentment is not synonymous with material consumption (Narada, 1988). More recently, Maslow (1970) and others have identified hierarchies of needs that provide psychic satisfaction, beyond mere goods and services. Alkire (2002) reviews the widely varying dimensions of human development (see Section 2.4.2 on indicators). Economic sustainability The modern concept underlying economic sustainability seeks to maximize the flow of income that could be generated while at least maintaining the stock of assets (or capital) which yield this income (Maler, 1990; Solow, 1986). Fisher (1906) defined capital as ‘a stock of instruments existing at an instant of time’ and income as ‘a stream of services flowing from this stock of wealth’. Hicks (1946) argued that people’s maximum sustainable consumption is ‘the amount that they can consume without impoverishing themselves’. Economic efficiency plays a key role in ensuring optimal consumption and production (Box 2.2). Many argue that unrestrained economic growth is unsustainable, and point out practical limitations in applying the economic sustainability rule without additional environmental and social safeguards (see weak and strong sustainability in Section 2.3.2). Problems arise in defining the kinds of capital to be maintained (e.g. manufactured, natural, human and social capital have been identified) and their substitutability (see Section 2.2.2). Often, it is difficult to value these assets and the services they provide, particularly in the case of ecological and social resources (Munasinghe, 1992a). Even key economic assets may be overlooked,


Box 2.3 Key concepts in mainstream economics Mainstream economics today is basically neoclassical economics, although less known alternatives exist, including Austrian, classical, evolutionary, institutional, Marxist and socialist economics. Neoclassical economics is based on several fundamental assumptions. (1) Individual consumers maximize their utility (or welfare) by making rational choices among goods and services available in the market – this is known as the consumer theory. (2) Individual producers maximize their profits by making rational choices about what outputs to produce, what inputs to use and what technologies to adopt – this is the producer theory. (3) Individuals act independently, using full and accurate information – known as market behaviour.

These ideas underlie the concept of ‘general equilibrium’ (associated with Walras), where supply and demand for goods and services balance in all markets. Another key concept involves Pareto (economic) efficiency or optimality, which is a (Walrasian) equilibrium state where no further actions are possible that could make any single person better off (i.e. welfare improvement) without making someone else worse off. Economic efficiency in the real world is measured in relation to the ideal of Pareto optimality (Bator, 1957). Within the neoclassical economics framework, one intellectual foundation of ‘capitalism’ is the assumption of ‘perfect competition’. Here, large numbers of consumers compete for homogeneous goods and services, which are produced by many small firms. Neither consumers nor producers have market control – i.e. they must accept the market price. Under certain restrictive conditions, perfect competition could lead to a Pareto efficient outcome, which has become a major argument in favour of ‘free markets’. In this economist’s ideal world, (efficient) prices reflect the true marginal social costs and ensure both efficient allocation of productive resources to maximize output and efficient consumption choices that maximize consumer utility. Neoclassical assumptions underlie standard microeconomics – e.g. consumer theory, producer theory and cost–benefit analysis (see Chapter 3). Mainstream macroeconomic models (e.g. the simple IS-LM analysis described in Section 7.3), are also based on the neoclassical synthesis. The latter combines classical models (based on long-term Walrasian market equilibrium, characterized by full employment and price stability) with Keynesian theory (which focuses on short-run disequilibrium phenomena such as unemployment and inflation). A serious issue arises because the existing income distribution is ignored when strict efficiency criteria are used to determine economic welfare. The result may be unethical, socially inequitable and politically unacceptable, especially if there are large income disparities. For example, the cost-benefit criterion (see Section 3.2) accepts all projects whose net benefits are positive (i.e. aggregate benefits exceed costs). It is based on the weaker ‘quasi’-Pareto condition, which assumes that net benefits could be redistributed

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from the potential gainers (based on their willingness-to-pay) to the losers (based on their willingness-to-accept), so that no one is worse off than before. Such transfers are rarely practical. More generally, interpersonal comparisons of (monetized) welfare are difficult to make – both within and across nations, and over time. Cost–benefit analysis assumes that the marginal utility of each unit consumed is the same for a given individual and across individuals (irrespective of the levels of consumption). Perfectly competitive conditions rarely exist in the real world. Distortions due to monopoly practices, externalities (e.g. environmental impacts that are not internalized; see Chapter 3), interventions in the market process through taxes and duties and subsidies all result in market prices for goods and services that diverge from efficient values. Thus, neither consumption nor production decisions may be efficient. Moreover, the rational actor assumption is also questionable (see Box 2.2). Neoclassical economists have responded to such criticisms, e.g. with ‘second-best’ changes, when ideal (first-best) conditions do not apply. One example relevant to sustainomics is the use of shadow prices (instead of market prices) to determine optimal investment decisions (via cost–benefit analysis) and pricing policies (see Chapter 3). Chapters 7 to 9 also describe examples which seek to incorporate environmental and social concerns into macroeconomic models.

e.g. where non-market transactions dominate. Uncertainty, irreversibility and catastrophic collapse also pose difficulties (Pearce and Turner, 1990). Many commonly used microeconomic approaches rely heavily on marginal analysis based on small perturbations (e.g. comparing incremental costs and benefits of economic activities). From the viewpoint of resilience theory (see Section 2.2.2), such a mildly perturbed system soon returns to its dominant stable equilibrium and thus there is little risk of instability. Thus, marginal analysis assumes smoothly changing variables and is not appropriate for analysing large changes, discontinuous phenomena and rapid transitions among multiple equilibria. Economic system resilience is better judged by the ability to deliver key economic services and allocate resources efficiently in the face of major shocks (e.g. the 1973 oil price shock or severe drought). More recent work is exploring the behaviour of large, non-linear, dynamic and chaotic systems in relation to system vulnerability and resilience.

2.2.2 Environmental aspects Unlike traditional societies, modern economies have only recently acknowledged the need to manage scarce natural resources in a prudent manner – because human welfare ultimately depends on ecological services (MA, 2003). Ignoring safe ecological limits will increase the risk of undermining long-run prospects for development. Munasinghe (2002b) reviews how economic development and the environment have been linked in the literature since Malthus. Dasgupta and Maler (1997) point out that, until the 1990s, the mainstream development literature rarely mentioned the topic of environment (Chenery and Srinivasan, 1988–1989;


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Dreze and Sen, 1990; Stern, 1989). More recent examples of the growing literature on the theme of environment and sustainable development include books by Faucheux, Pearce and Proops (1996), describing models of sustainable development, and Munasinghe, Sunkel and de Miguel (2001), addressing the links between growth and environment. Several researchers argue that environmental and geographic factors have been key drivers of past growth and development (Diamond, 1997; Sachs, 2001). Environmental sustainability The environmental interpretation of sustainability focuses on the overall viability and health of living systems – defined in terms of a comprehensive, multiscale, dynamic, hierarchical measure of resilience, vigour and organization (Costanza, 2000). These ideas apply to both natural (or wild) and managed (or agricultural) systems, and cover wilderness, rural and urban areas. Resilience is the potential of a system state to maintain its structure/function in the face of disturbance (Holling and Walker, 2003; Ludwig, Walker and Holling, 1997; Pimm, 1991). An ecosystem state is defined by its internal structure and set of mutually reenforcing processes. Holling (1973) originally defined resilience as the amount of change that will cause an ecosystem to switch from one system state to another. Resilience is also related to the ability of a system to return to equilibrium after a disruptive shock (Pimm, 1984). Petersen, Allen and Holling (1998) argue that the resilience of a given ecosystem depends on the continuity of related ecological processes at both larger and smaller spatial scales (Box 2.2). Adaptive capacity is an aspect of resilience that reflects a learning element of system behaviour in response to disturbance. Natural systems tend to be more vulnerable to rapid external changes than social systems – the latter may be able to plan their own adaptation. Vigour is associated with the primary productivity of an ecosystem. It is analogous to output and growth as an indicator of dynamism in an economic system. Organization depends on both complexity and structure of an ecological or biological system. For example, a multicellular organism like a human being is more highly organized (having more diverse subcomponents and interconnections among them) than a singlecelled amoeba. Higher states of organization imply lower levels of entropy. Thus, the second law of thermodynamics requires that the survival of more complex organisms depends on the use of low-entropy energy derived from their environment, which is returned as (less useful) high-entropy energy. The ultimate source of this energy is solar radiation. In this context, natural resource degradation, pollution and loss of biodiversity are detrimental because they increase vulnerability, undermine system health and reduce resilience (Munasinghe and Shearer, 1995; Perrings and Opschoor, 1994). Ciriacy-Wantrup (1952) introduced the idea of safe thresholds (also related to carrying capacity), which is important – often to avoid catastrophic ecosystem collapse (Holling, 1986; Ekins, Folke and de Groot, 2003). Sustainability may be understood also in terms of the normal functioning and longevity of a nested hierarchy of ecological and socioeconomic systems, ordered according to scale (see Box 2.2). Sustainable development goes beyond the static maintenance of the ecological status quo. A coupled ecological–socioeconomic system may evolve so as to maintain a level of

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biodiversity that will ensure long-term system resilience. Such an ecological perspective supercedes the narrower economic objective of protecting only the ecosystems on which human activities directly depend. Sustainable development demands compensation for opportunities foregone by future generations, because today’s economic activity changes biodiversity in ways that will affect the flow of vital future ecological services. The linkage between, and co-evolution of, socioeconomic and ecological systems also underlines the need to consider their joint sustainability; see Section 2.3.1. In brief, what ecological (and linked socioeconomic) systems need is improved system health and the dynamic ability to adapt to change across a range of spatial and temporal scales, rather than the conservation of some ‘ideal’ static state (see Box 2.2).

2.2.3 Social aspects Social development usually refers to improvements in both individual well-being and the overall social welfare that result from increases in social capital – typically, the accumulation of capacity for individuals and groups of people to work together to achieve shared objectives (Coleman, 1990; Putnam, 1993). Social capital is the resource people draw upon in pursuit of their aspirations and is developed through networks and connectedness, membership of more formalized groups and relationships of trust, reciprocity and exchanges. The institutional component of social capital refers mainly to the formal laws as well as traditional or informal understandings that govern behaviour, while the organizational component is embodied in the entities (both individuals and social groups) that operate within these institutional arrangements. For our purposes, we assume that human capital (e.g. education, skills, etc.) and cultural capital (e.g. social relationships and customs) are also included within social capital – although fine distinctions do exist. The quantity and quality of social interactions that underlie human existence, including the level of mutual trust and extent of shared social norms, help to determine the stock of social capital. Thus, social capital tends to grow with greater use and erodes through disuse, unlike economic and environmental capital, which are depreciated or depleted by use. Furthermore, some forms of social capital may be harmful (e.g. cooperation within criminal gangs may benefit them, but impose far greater costs on the larger community). Equity and poverty alleviation are important; see Section 2.3.5. Thus, social goals include protective strategies that reduce vulnerability, improve equity and ensure that basic needs are met. Future social development will require sociopolitical institutions that can adapt to meet the challenges of modernization – which often destroy traditional coping mechanisms that disadvantaged groups have evolved in the past. From the poverty perspective, social capital may be classified into three basic types that overlap in practice: bonds, bridges and links (discussed later in Box 16.1). Bonding social capital is centred on relations of trust and common activities among family, friends and groups within the same community. It helps to create broad-based social solidarity, meet the daily needs of the poor and reduce their risk vulnerability. Bridging social capital relies on individuals and local groups building connections with nearby communities, as well as


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regional and national organizations that share similar values or interests (e.g. credit organizations and livelihood networks, which provide social protection and job opportunities). Such bridging has facilitated the emergence of many non-governmental and civil society organizations. Linking social capital is built on influential associations – e.g. having access to powerful people or organizations such as government ministries and international agencies. Such links are useful to facilitate access to benefits (e.g. loans, jobs, help with small enterprise development, etc.) and to lift people out of poverty. Trust, power and security are also important elements of cognitive social capital. Levels of trust in individuals, groups or institutions provide an indication of the extent of cooperation. Where networks are weak, people generally have lower levels of trust. Power is usually equated with influence and connections. If leaders are distant and do not deliver beneficial changes, people do not recognize them as powerful. Leaders often fail to link with the poorest groups, thereby disempowering them further. Secure relationships play a key role in good governance. Analysis of the dynamics of community relations provides a social map that allows practitioners to tailor specific programmes to targeted groups, thereby creating better opportunities for the poor to participate in decision making. Recent research has emphasized the role of institutions in explaining differences among nations in terms of economic growth or stagnation; i.e. how behavioural norms govern social conduct, which ultimately determines economic behaviour (Acemoglu, Johnson and Robinson, 2001; North, 1990). Social sustainability Social sustainability parallels the ideas discussed earlier regarding environmental sustainability (UNEP, IUCN and WWF, 1991). Reducing vulnerability and maintaining the health (i.e. resilience, vigour and organization) of social and cultural systems, and their ability to withstand shocks, is important (Bohle, Downing and Watts, 1994; Chambers, 1989; Ribot, Najam and Watson, 1996). Enhancing human capital (through education) and strengthening social values, institutions and equity will improve the resilience of social systems and governance. Many such harmful changes occur slowly, and their long-term effects are overlooked in socioeconomic analysis. Preserving cultural capital and diversity across the globe is important – there are about 6000 cultural groups with different languages worldwide, while indigenous cultures (as opposed to state cultures) may represent over 90% of global cultural diversity (Gray, 1991). Munasinghe (1992a) drew parallels between the respective roles of biodiversity and cultural diversity in protecting the resilience of ecological and social systems and the interlinkages between them. Several subsequent reports from international organizations have highlighted cultural diversity (UNDP, 2004; UNESCO, 2001). Strengthening social cohesion and networks of relationships, and reducing destructive conflicts, are also integral elements of this approach. An important aspect of empowerment and broader participation is subsidiarity – i.e. decentralization of decision making to the lowest (or most local) level at which it is still effective. Understanding the links that radiate out from poor communities, and their interface with agencies and government, is critical for building connections and channelling resources

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more directly to make social development more sustainable. Emphasis has sometimes been placed on the formation of new community-level organizations, which occasionally undermine existing networks and local groups – ultimately causing the locals to feel that they have no stake or ownership in the project. Thus, the focus is shifting toward improving governance by giving poor people the right to participate in decisions that affect them. Working with existing community-based social capital generates pathways to lever people upward from poverty. It also results in a more sustainable link with communities and creates opportunities for more meaningful participation.

2.3 Integration of economic, social and environmental elements 2.3.1 Need for integration It is important to integrate and reconcile the economic, social and environmental aspects within a holistic and balanced sustainable development framework. Economic analysis has a special role in contemporary national policy making, since many important decisions fall within the economic domain. Unfortunately, mainstream economics, which is used for practical policy making, has often ignored the environmental and social dimensions of sustainable development. However, there is a small but growing body of literature which seeks to address such shortcomings – e.g. the journals Ecological Economics and Conservation Ecology. As a prelude to integration, it is useful to compare the concepts of ecological, social and economic sustainability. One useful idea is that of the maintenance of the set of opportunities, as opposed to the preservation of the value of the asset base (Githinji and Perrings, 1992). In fact, if preferences and technology vary through successive generations, merely preserving a constant value of the asset base becomes less meaningful. By concentrating on the size of the opportunity set, the importance of biodiversity conservation becomes more evident for the sustainability of an ecosystem. The preservation of biodiversity allows the system to retain resilience by protecting it from external shocks, while the maintenance of stocks of manufactured capital protects future consumption. Differences emerge because economics indicates that a society that consumes its fixed capital without replacement is not sustainable, whereas, using an ecological approach, unsustainable loss of biodiversity and resilience implies a reduction in the self-organization of the system, but not necessarily a loss in productivity. In the case of social systems, resilience depends, to a certain extent, on the capacity of human societies to adapt and continue functioning in the face of stress and shocks. Thus, linkages between sociocultural and ecological sustainability emerge through their interactions, organizational similarities between human societies and ecological systems and the parallels between biodiversity and cultural diversity. From a longer-term perspective, the concept of co-evolution of social, economic and ecological systems within a larger, more complex, adaptive system, provides useful insights regarding the harmonious integration of the various elements of sustainable development; see Figure 2.1 and Chapter 4 (Costanza et al., 1997; Munasinghe, 1994a; Norgaard, 1994).


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Optimality and durability are two broad approaches that help to integrate the economic, environmental and social dimensions of sustainable development. While there are overlaps between the two methods, the main thrust is somewhat different in each case. Uncertainty often plays a key role in determining which approach would be preferred. For example, a system modeller expecting relatively steady and well ordered conditions may pursue an optimal solution that attempts to control, and even fine-tune, theoretical outcomes. Meanwhile, a subsistence farmer facing chaotic and unpredictable circumstances might opt for a more durable and practical response that simply enhances survival prospects.

2.3.2 Optimality The optimality-based approach has been widely used in economic analysis to generally maximize welfare (or utility), subject to the requirement that the stock of productive assets (or welfare itself) is non-decreasing in the long term This assumption is common to most sustainable economic growth models, as reviewed by Pezzey (1992) and Islam (2001b). The essence of the approach is illustrated by the simple example of maximization of the flow of aggregate welfare (W), cumulatively discounted over infinite time (t), as represented by the following expression: Z 1 Max WðC; ZÞert dt; 0

where W is a function of C (the consumption rate) and Z (a set of other relevant variables), and r is the discount rate. Further side constraints may be imposed to satisfy sustainability needs, e.g. non-decreasing stocks of productive assets (including natural resources). The welfare-maximizing optimality-based approach underlies commonly used economic techniques such as shadow pricing and cost–benefit analysis (see Section 3.2). Some ecological models also optimize variables such as energy use, nutrient flow or biomass production – giving more weight to system vigour as a measure of sustainability. In economic models, utility is measured mainly in terms of the net benefits of economic activities, i.e. the benefits minus the costs (see Chapter 3 and Freeman (1993) and Munasinghe (1992a)). More advanced economic optimization methods seek to include environmental and social variables (e.g. by valuing environmental externalities, system resilience, etc.). However, given the difficulties of valuing such ‘non-economic’ assets, the costs and benefits associated with market-based activities dominate in most economic optimization models. Within this framework, the optimal growth path maximizes economic output, while sustainability rules are met by ensuring non-decreasing stocks of assets (or capital). Some analysts support a ‘strong sustainability’, which requires separate preservation of each type of critical asset (e.g. manufactured, natural, sociocultural and human capital), assuming that they are complements rather than substitutes (Pearce and Turner, 1990). Others have argued for ‘weak sustainability’, which seeks to maintain the aggregate monetary value of total

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stocks of all assets, assuming that various asset types may be valued and that there is some degree of substitutability among them (Nordhaus and Tobin, 1972). Side constraints are often necessary, because the underlying basis of economic valuation, optimization and efficient use of resources may not be easily applied to ecological objectives such as protecting biodiversity and improving resilience, or to social goals such as promoting equity, public participation and empowerment. Thus, such environmental and social variables cannot be easily combined into a single-valued objective function with other measures of economic costs and benefits (see Section 2.4.2 and Chapter 3). Moreover, the price system (which has time lags) might fail to anticipate reliably irreversible environmental and social harm and non-linear system responses that could lead to catastrophic collapse. In such cases, non-economic measures of environmental and social status would be helpful, e.g. area under forest cover and incidence of conflict (Hanna and Munasinghe, 1995a, 1995b; Munasinghe and Shearer, 1995; UNDP, 1998; World Bank, 1998). The constraints on critical environmental and social indicators are proxies representing safe thresholds, which help to maintain the viability of those systems. Multicriteria analysis facilitates trade-offs among a variety of non-commensurable variables and objectives (see Chapter 3). Risk and uncertainty will also necessitate the use of decision analysis tools. Recent work has underlined the social dimension of decision science by pointing out that risk perceptions are subjective and depend on the risk measures used as well as other factors, such as ethnocultural background, socioeconomic status and gender (Bennet, 2000).

2.3.3 Durability The second broad integrative approach focuses primarily on sustaining the quality of life, e.g. by satisfying environmental, social and economic sustainability requirements. Such a framework favours ‘durable’ development paths that permit growth, but are not necessarily economically optimal. There is more willingness to trade-off some economic optimality for the sake of greater safety, in order to stay within critical environmental and social limits, e.g. among increasingly risk-averse and vulnerable societies or individuals who face chaotic and unpredictable conditions (see the precautionary principle in Chapter 5). The economic constraint might be framed in terms of maintaining consumption levels (defined broadly to include environmental services, leisure and other ‘non-economic’ benefits), i.e. per capita consumption that never falls below some minimum level or is non-declining. The environmental and social sustainability requirements may be measured by indicators of ‘state’ relating to the durability or health (resilience, vigour and organization) of ecological and socioeconomic systems. For example, consider a simple durability index (D) for an ecosystem measured in terms of its expected lifespan (in a healthy state) as a fraction of the normal lifespan (see Box 2.2). We might specify D = D(R, V, O, S) to indicate the dependence of durability on resilience (R), vigour (V), organization (O) and the state of the external environment (S) – especially in relation to potentially damaging shocks. Further interaction between the sustainability of social and ecological systems may be relevant, e.g. social


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conflict could exacerbate damage to ecosystems and vice versa. For example, long-standing social norms in many traditional societies have helped to protect the environment (Colding and Folke, 1997). Durability encourages a holistic systemic viewpoint, which is important in sustainomics analysis. The self-organizing and internal structure of ecological and socioeconomic systems makes ‘the whole more durable (and valuable) than the sum of the parts’ (see Chapter 4). A narrow measure of merit based on marginal analysis of individual components may be misleading (Schutz, 1999). For example, it is more difficult to value the integrated functional diversity in a forest ecosystem than the individual species of trees and animals. Therefore, the former is more likely to fall victim to market failure (as an externality). Furthermore, use of simple environmental shadow prices could lead to homogenization and reductions in system diversity (Perrings, Maler and Folke, 1995). Systems analysis helps to identify the benefits of cooperative structures and behaviour, which a more partial analysis may neglect. Durability is also linked to the well known concept of ‘satisficing’ behaviour, where individuals seek to reach a minimum level of satisfaction, without striving to achieve the maximum possible value (Simon, 1959). The possibility of many durable paths favours simulation-based methods, including consideration of alternative world views and futures (rather than one optimal result). This approach is consonant with recent research on integrating human actors into ecological models (Ecological Economics, 2000). Key elements include multiple-agent modelling, to account for heterogeneous behaviour, recognition of bounded rationality, leading to different perceptions and biases, and emphasis on social links, which give rise to responses such as imitation, reciprocity and comparison. In the durability approach, sustainability constraints could be met by maintaining stocks of assets (as for optimality). Here, the various forms of capital are viewed as a bulwark that decreases vulnerability to external shocks and reduces irreversible harm, rather than mere accumulations of assets that produce economic outputs. System resilience, vigour, organization and ability to adapt will depend dynamically on the capital endowment as well as on the magnitude and rate of change of a shock.

2.3.4 Complementarity and convergence of optimality and durability National economic management provides good examples of how the two approaches complement one another. For example, economy-wide policies involving both fiscal and monetary measures (e.g. taxes, subsidies, interest rates and foreign exchange rates) might be optimized on the basis of quantitative macroeconomic models. Nevertheless, decision makers inevitably modify these economically ‘optimal’ policies before implementing them, to take into account other sociopolitical considerations based more on durability (e.g. protection of the poor, regional factors), which facilitate governance and stability. Setting an appropriate target for future global greenhouse gas (GHG) emissions (and corresponding GHG concentration) provides another useful illustration of the interplay of the durability and optimality approaches (see Chapter 5 and Munasinghe (1998a)).

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The complementarity and convergence of the two approaches may be practically realized in several ways. First, waste generation should be limited to rates less than or equal to the assimilative capacity of the environment. Second, the utilization of scarce renewable resources should be limited to rates less than or equal to their natural rate of regeneration. Third, non-renewable resources need to be managed in relation to the substitutability between these resources and technological progress. Both wastes and natural-resource-input use might be reduced by moving from the linear throughput to the closed-loop mode. Thus, factory complexes could be designed in clusters – based on the industrial ecology concept – to maximize the circular flow of materials and recycling of waste among plants. Finally, additional aspects should be considered (at least in the form of safe limits or constraints), including inter- and intragenerational equity (poverty alleviation), pluralistic and consultative decision making and enhanced social values and institutions. Greenhouse gas mitigation provides one example of how such an integrative framework could help to incorporate climate change policies within a national sustainable development strategy. The rate of total GHG emissions (G) may be decomposed by means of the following identity: G ¼ ½Q=P½Y=Q½G=Y P;

(2:1)

where [Q/P] is quality of life per capita; [Y/Q] is the material consumption required per unit of quality of life; [G/Y] is the GHG emission per unit of consumption; and P is the population. A high quality of life [Q/P] can be consistent with low total GHG emissions [G], provided that each of the other three terms on the right-hand side of the identity could be minimized (see ‘tunnelling’ in Section 2.5.2). Reducing [Y/Q] implies ‘social decoupling’ (or ‘dematerialization’), whereby satisfaction becomes less dependent on material consumption through changes in tastes, behaviour and values – more sustainable consumption. Similarly, [G/Y] may be reduced by ‘technological decoupling’ (or ‘decarbonization’), which reduces the intensity of GHG emissions in both consumption and production. Finally, population growth needs to be reduced, especially where emissions per capita are already high. The links between social and technological decoupling need to be explored (IPCC, 1999) – changes in public perceptions and tastes could affect the directions of technological progress and influence the effectiveness of mitigation and adaptation capacity and policies. A range of economic and social policy instruments may be used to make both consumption and production patterns more sustainable. Policy tools include market incentives and pricing, legislation and controls, improved technological alternatives and consumer education (see Chapters 5 and 14). Climate change researchers are currently exploring the application of large and complex integrated assessment models, or IAMs, which contain coupled submodels that represent a variety of ecological, geophysical and socioeconomic systems (IPCC, 1997). Both optimality and durability might be appropriately applied to the various submodels within an IAM.


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2.3.5 Poverty, equity, population and sustainable natural resource use This section examines key issues in the nexus of poverty–equity–population–natural resources from a holistic sustainomics perspective. Dimensions of equity and poverty Equity and poverty are two important issues, which have mainly social and economic dimensions, and also some environmental aspects (see Figure 2.1). Compelling worldwide statistics were given in Section 1.2. Meanwhile, income disparities are worsening – the per capita ratio between the richest and the poorest 20 percentile groups was 30 to 1 in 1960 and over 60 to 1 by 2000. Equity is an ethical and people-oriented concept with primarily social and some economic and environmental dimensions. It focuses on the fairness of both the processes and outcomes of decision making. The equity of an action may be assessed in terms of several approaches, including parity, proportionality, priority, utilitarianism and Rawlsian distributive justice. Rawls (1971) stated that ‘Justice is the first virtue of social institutions, as truth is of systems of thought.’ Societies seek to achieve equity by balancing and combining several of these criteria. Economic policies aiming to increase overall human welfare have been used for poverty alleviation, improved income distribution and intragenerational (or spatial) equity (Durayappah, 1998; Sen, 1981, 1984). Brown (1998) points out shortcomings in the utilitarian approach, which underlies the economic approach to equity. Broadly speaking, economic rules provide guidance on producing and consuming goods and services more efficiently, but are unable to choose the most equitable outcome among alternative patterns of efficient consumption. Equity principles provide better tools for making judgements about such choices. Social equity is also linked to sustainability, because highly skewed or unfair distributions of income and social benefits are less likely to be acceptable or lasting in the long run. Equity will be strengthened by enhancing pluralism and grass-roots participation in decision making, as well as by empowering disadvantaged groups (defined by income, gender, ethnicity, religion, caste, etc.) (Rayner and Malone, 1998). In the long term, considerations involving intergenerational equity and safeguarding the rights of future generations are key factors. In particular, the economic discount rate plays a key role with respect to both equity and efficiency aspects (Arrow et al., 1995b). Box 2.4 reviews links between social equity and economic efficiency within the sustainomics framework. Equity in the environmental sense has received more attention recently because of the disproportionately greater environmental damages suffered by disadvantaged groups. Thus, poverty alleviation efforts (that traditionally focused on raising monetary incomes) are being broadened to address the degraded environmental and social conditions facing the poor. Martinez-Allier (2004) argues that the poor who rely more directly on natural resources are often good environmental managers, whereas the rich impose a more harmful environmental footprint through the indirect effects of their consumption. Munasinghe (1997)

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Box 2.4 Interactions between social equity and economic efficiency Conflicts between economic efficiency and equity may arise during the definition, comparison and aggregation of the welfare of different individuals or nations. For example, efficiency implies maximization of output subject to resource constraints, assuming that increases in average income per capita will make most or all individuals better off. However, if the income distribution becomes less equitable, overall welfare might drop, depending on how welfare is defined in relation to income distribution. Conversely, total welfare may increase if policies and institutions ensure appropriate resource transfers – typically from rich to poor. Aggregating and comparing welfare across and within different countries is also a disputable issue. Gross National Product (GNP) is a measure of the total economic output of a country and does not represent welfare directly. Aggregating GNP within a nation may not be a valid measure of total welfare. However, national economic policies frequently focus more on GNP growth rather than its distribution, implying that additional wealth is equally valuable to rich and poor alike, or that there are mechanisms to redistribute wealth in an equitable way. Attempts have been made to incorporate equity considerations within an economic framework, by weighting costs and benefits so as to favour the poor. Although systematic procedures exist for determining such weights, often the arbitrariness in assigning weights has caused practical problems. At the same time, it should be recognized that all decision-making procedures do assign weights (arbitrarily or otherwise). For example, progressive personal income taxes are designed to take proportionately more from the rich. On the other hand, traditional cost–benefit analysis based on economic efficiency assigns the same weight to all monetary costs and benefits – irrespective of income levels. More pragmatically, in most countries the tension between economic efficiency and equity is resolved by keeping the two approaches separate, e.g. by maintaining a balance between maximizing GNP and establishing institutions and processes charged with redistribution, social protection and provision of basic needs. The interplay of equity and efficiency at the international level is shown later, in the climate change case study.

challenges the common belief that poverty and population growth per se are harmful to nature, which conceals a crucial equity issue – the poor, although more numerous, consume far less than the rich (see below). Ethics and equity in relation to climate change are discussed in Section 5.2.2. In summary, both equity and poverty have not only economic, but also social and environmental dimensions, and therefore they need to be assessed using a comprehensive set of indicators (rather than income distribution alone). From an economic policy perspective, emphasis needs to be placed on expanding employment and gainful opportunities for poor people through growth, improving access to markets and increasing both assets and education. Social policies would focus on empowerment and inclusion, by making institutions


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more responsive to the poor and removing barriers that exclude disadvantaged groups. Environmentally related measures to help poor people might seek to reduce their vulnerability to disasters and extreme weather events, crop failures, loss of employment, sickness, economic shocks, etc. Thus, an important objective of poverty alleviation is to provide poor people with assets (e.g. enhanced physical, human and financial resources) that will reduce their vulnerability. Such assets increase the capacity for both coping (i.e. making short-run changes) and adapting (i.e. making permanent adjustments) to external shocks (Moser, 1998). The foregoing ideas merge quite naturally with the sustainable-livelihoods approach to poverty alleviation. We identify three key aspects of livelihoods that are important for the sustainability of poverty programmes (Munasinghe, 2003). First, there are gainful activities that people engage in, ranging from formal, full-time employment to seasonal, informal and ad hoc jobs, which provide only a bare subsistence income in both urban and rural settings. Second, access to productive assets and the services they provide are important. Economic assets consist of familiar manufactured capital such as machines and buildings. Key environmental assets, which draw on the base of natural capital, are often overlooked. Social capital is equally important and includes social, political and other processes and institutions that facilitate human interactions; they are linked to values, culture and behavioural norms. Third, there are rights and entitlements, which are especially important for poor and destitute groups to meet basic needs for survival (Sen, 1981). Other authors have identified five types of assets that are important for sustainable livelihoods: human, social, natural, physical and financial (Carney, 1998). An even broader non-anthropocentric approach to equity involves the concept of fairness in the treatment of non-human forms of life or even inanimate nature. One view asserts that humans have the responsibility of prudent ‘stewardship’ (or ‘trusteeship’) over nature, which goes beyond mere rights of usage (Brown, 1998). Population and natural resource use The linkage between population and natural resource use is also complex and needs to be studied in the context of poverty and equity (Munasinghe, 1995a). Sustainomics encourages us to take a balanced view, where people are seen as a resource, not necessarily an unsustainable burden. One general belief is that the growth of poor population is harmful to natural resources, starting with Malthus (1798); see Section 7.1.1. For example, a widely cited article on the conservation of wild living resources (Mangel et al., 1996) asserts provocatively that ‘the only practicable way to reduce human per capita resource demand is to stabilize and then decrease the human population’ (our emphasis) . This proposition is misleading and detracts from the overall content of an otherwise authoritative and comprehensive paper. No convincing evidence exists to link per capita natural-resource demand with population size. Even the link between total resource use and population is complex and cannot be captured adequately by a simple statement. Consider the earlier equation (2.1), rewritten to show total natural-resource use as follows: N = [N/P] × P, where P is the population and [N/P] is per capita natural-resource use. An exclusive focus on population control is one-sided, because high levels of per capita

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consumption are as much to blame for resource depletion as simple population growth. Currently, a mere 15% of the world’s rich population consume over 16 times as much as the almost 60% of the poor population (and will do so for the foreseeable future). A more equitable and balanced viewpoint would recognize the implications of both population and per capita consumption for sustainability. Furthermore, the growth rates of per capita consumption and population among the rich should be matters of greater concern than the same indices among the poor. Environmental degradation, population and poverty are known to form a nexus with complex interactions (see Section 4.2.6). The poor are the most frequent victims of both pollution and resource degradation usually caused by the rich – which is inequitable. At the same time, there are macrocircumstances in which the landless poor are forced to encroach on fragile lands, eventually degrading their own environment (Munasinghe and Cruz, 1994). A comprehensive multiagency report argued recently that poverty alleviation requires environmental protection, and that both objectives should be pursued simultaneously (DFID et al., 2002). Grima, Horton and Kant, (2003) discuss reconciliation of the opposing viewpoints of ecologists favouring natural-resource sustainability and economists promoting development and poverty alleviation, under four different themes – institutions, ecotourism, measurement indicators and fragile lands. Meanwhile, population growth itself depends on many factors, including not only the highly visible elements such as family planning programmes, but also deeper underlying factors such as education level (especially of women), the status of women, family income, access to basic needs and financial security (Dasgupta, 1993). A simple mathematical exposition suggests that the common wisdom linking population growth with natural resource depletion is not necessarily as straightforward as it seems (Munasinghe, 1997). Consider a society which has a population P and a stock of natural resources N. One useful indicator of the sustainability of natural-resource stocks would be the ratio R = N/P. More specifically, one might seek a development path in which this ratio was non-decreasing. Thus, sustainability would require that dR/dt ≥ 0. A more convenient sustainability rule may be defined as follows: S¼ðdR=dtÞ = R ¼ ½ðd=dtÞ ðW=PÞ=½W=P0: It is possible to decompose the measure S to show the distinct effects of growth in natural resource stocks and growth in population. Assuming that N = N(P, t) and P = P(t), we obtain S ¼ ½ð@W=@tÞ=N f½ðdP=dtÞ=P½1 eg; where e ¼ ð@N=@PÞ=ðW=PÞ: Clearly, the first term […] is positive if (∂W/∂t) > 0; that is, S rises as natural-resource stocks increase over time, holding the population constant. However, the sign of the second term {…} depends on the sign of both (dP/dt) and (1 – e). Thus, reducing the population (dP/dt < 0) will increase sustainability S only if e < 1. The opposite condition e > 1 is more likely to prevail if N/P is low to begin with and ∂N/∂P is relatively high, e.g. if mild population growth stimulates greater efforts toward protecting and increasing resource stocks. One example might be a community living in an arid area. If the human population dwindles, the


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natural progress of desertification could well proceed unimpeded. By contrast, a growing and thriving population (with increasing income levels) is likely to devote more efforts toward environmental protection, ensuring that the condition e >1 is maintained. Rapid declines in population growth rates have serious demographic implications – as many countries are discovering today. The base of the population pyramid shrinks as birth rates drop and the population ages, leaving a smaller group of productive young people to support an increasing fraction of elderly and dependent persons. Some countries have responded by encouraging immigration to increase the labour force. The policy implications of an aging population include a radical rethinking of many serious issues, including the retirement age, encouraging more productive activity among the elderly, rebalancing social insurance contributions and pension payments, etc. The foregoing argument may be summarized as follows. While it is ‘fashionable’ to assume automatically that people are a threat to natural resources and sustainability, a good case may be made for considering human beings as a valuable resource for sustainable development (see Section 4.3.2). Human and natural resources are complementary. Furthermore, human attitudes toward the environment and their patterns of economic activity are at least as important as the number of people. From a sustainomics perspective, if scarce environmental resource stocks are at risk, building human and social capital through enhanced education, training, health and other social services could be the key to unlocking the potential of poor people and converting a perceived liability into an asset. The third element of the sustainable development triangle (economic resources) could also play a role through improved technology to reduce the pressure on mineral and living wild resources. To conclude, if both per capita resource demand and population are examined more evenhandedly, some promising options for the conservation of natural resources will emerge. A background factor that cannot be ignored is that economic growth is a prime imperative for developing countries, especially ones with large numbers of poor and destitute people. Section 2.5 shows how growth could be re-structured to make development more sustainable and how policies might be tailored to find a more sustainable path or ‘tunnel’ (see Figure 2.4).

2.4 Tools and methods for integrated analysis and assessment Some important tools and methods that may be used for integrated analysis and assessment are summarized below. Given the vast scope of sustainable development, the ‘tool kit’ is eclectic and by no means exhaustive. The idea is to provide the sustainomics practitioner with a selection of key methods. Later chapters provide practical applications, indicating tools that are appropriate under various circumstances.

2.4.1 Action Impact Matrix The Action Impact Matrix (AIM) is a multistakeholder consultative approach that facilitates the integration of the social, economic and environmental dimensions of

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development, identifies and prioritizes key interactions among them and determines policies and projects that make development more sustainable. The method has been widely used since the early 1990s, and was originally presented as part of the sustainomics framework at the 1992 Rio Earth Summit (Munasinghe, 1992a). Initially, it was used to integrate a range of environmental and social concerns into development planning (Munasinghe, 1994a, 1997, 2002a; Munasinghe et al., 2006) and later was adapted to address specific issues such as climate change, energy and water (MIND, 2004; Munasinghe, 2002b; Munasinghe and Swart, 2005). Basic procedure Typically, the AIM is used as a strategic tool to understand better the interlinkages among critical elements, at the country-specific level: (a) major national development policies and goals and (b) key sustainable development vulnerabilities and issues, e.g. relating to economic sectors, ecological systems and social factors. The AIM process begins with an ex-ante analysis of the two-way linkages between the fundamental elements (a) and (b), i.e. the effects of (a) on (b) and vice versa. By explicitly linking development goals with key economic–environmental–social issues, the AIM identifies potential barriers to sustainable development and helps to determine the priority strategies that will overcome them. The approach uses a fully participative multistakeholder exercise to generate the AIM itself. Up to 50 analysts and experts are drawn from government, academia, civil society and the private sector; they represent various disciplines and sectors relevant to both sustainable development and other issues relevant to the exercise. Initially, the stakeholders interact intensively over a period of about two days to build a preliminary AIM. This participative process is as important as the product (i.e. the AIM), since important synergies and cooperative team-building activities emerge. The collaboration helps participants to understand better opposing viewpoints, resolve conflicts, build ownership and facilitate implementation of agreed policy remedies. On subsequent occasions, the updating or fine-tuning of the initial AIM can be achieved quickly by the same group, since they are already conversant with the methodology. For maximum effectiveness, the AIM workshop needs to be prepared carefully by trained instructors who conduct the exercise, documentation (e.g. AIM Guide), screening and pre-selection of a balanced group of participants and advance gathering of relevant background data. The AIM methodology draws on the basic principles and methods of the sustainomics framework described earlier in this chapter, including a focus on making development more sustainable (MDMS), balanced consideration of the sustainable development triangle, emphasis on transcending boundaries and full-cycle application of integrative tools – where the AIM plays a key role. Thus, the AIM is the key link from initial data gathering to practical policy application and feedback. The AIM process consists of the following key steps.


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Screening and problem identification (a) (b) (c) (d) (e)

Determine the most important development goals and policies (DG) – matrix rows. Determine key sustainable development vulnerabilities and issues (VI) – matrix columns. Determine the current status of VI – the matrix cells. Identify how DG might affect VI (matrix DEV) – the matrix cells. Identify how VI might affect DG (matrix VED) – the matrix cells.

Analysis, prioritization and remediation (f) Analyse and prioritize most important interactions and determine appropriate remedial policies and measures. (g) Perform more detailed studies and analysis of key interactions and policy options identified in step (f) above. (h) Update and refine steps (c)–(f) above.

Two matrices are derived, representing the two-way links: (1) matrix DEV – effects of development goals and policies on vulnerabilities and issues (DG ➔ VI); (2) matrix VED – effects of vulnerabilities and issues on development goals and policies (VI ➔ DG).

To summarize, AIM rows show national development goals and policies (DG) and columns indicate sustainable development vulnerabilities and issues (VI). The cells of the two preliminary matrices identify broad relationships between DG and VI, provide a quantitative and qualitative idea of the magnitudes of the key interactions, help to prioritize the most important links and facilitate formulation of appropriate policy responses. Meanwhile, the organization of the overall matrices facilitates the tracing of impacts, as well as the coherent articulation of the links among development activities (policies and projects). The AIM process is flexible and may be adapted in various ways to address different problems. Typical examples include the following. (1) Once the preliminary AIM is prepared, priority linkages may be pursued in two complementary ways: (a) upward link, where sustainable development vulnerability concerns are embedded in the macroeconomic and sectoral development strategy of a country via the medium- to longterm sustainable development path; (b) downward link, where sustainable development vulnerability concerns are integrated into the sub-national-level development strategy in the short- to medium-term, by carrying out sustainable development assessments aimed at making specific projects and policies more sustainable. (2) After completing a national-level AIM exercise, it is possible to apply the process at a sub-national or community level to fine-tune the analysis. (3) In a subsequent step, the impacts of other major external factors (such as climate change, natural disasters, rising oil prices, etc.) may be overlaid on the primary interaction between national development goals and policies (DG) and sustainable development vulnerabilities and issues (VI).

A practical application of the AIM procedure is provided in Section 6.3.

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2.4.2 Other methods and indicators Sustainable development assessment Sustainable development assessment (SDA) is an overarching methodology (with many components), which is used in evaluating investment projects (as well as programmes and policies) to ensure balanced analysis of both development and sustainability concerns. The ‘economic’ component of SDA is based on conventional economic and financial analysis (including cost–benefit analysis, as described below and in Chapter 3). The other two key components are environmental assessment (EA) and social assessment (SA); see Chapter 4 (World Bank, 1998). However, many other more specialized types of assessments may be included within an integrated SDA. Economic, environmental and social analyses need to be integrated and harmonized within SDA. Historically, EAs and SAs developed as separate processes. However, a full appreciation of all impacts requires a thorough understanding of all biophysical and social changes invoked as a result of planned interventions. Biophysical impacts have social impacts, and social changes also affect the biophysical environment. Recent work attempts to integrate biophysical and social impacts using a conceptual framework that is consistent with sustainomics, and this has led to a better understanding of the full extent of human impacts as well as the impact pathways that result from such interventions (see, e.g., Lee and Kirkpatrick, 2000). Green (2001) shows a practical application to mining. There is increasing interest in exploring various integrated approaches for SDA to facilitate research, policy planning and decision making (Boulanger and Brechet, 2002). Among the growing list of more specialized forms of appraisal are social assessment, health assessment, risk assessment, climate assessment, development impact assessment, poverty assessment, environmental assessment and gender impact assessment. This increase in the number of different components within the SDA framework has brought about an increasing number of difficulties. At the procedural level it has become more difficult to coordinate the timings of separate appraisals and to synchronize this with decisions made about the project. At the methodological level, there is an increasing likelihood of inconsistencies between the appraisal methods used, of interdependencies between certain types of impacts and of increasing difficulties in constructing an overall appraisal for use in decision making. At the organizational level, the workload has increased considerably, due to the burdens of managing and coordinating separate appraisals and multidisciplinary teams as part of the project planning and management process. The weaknesses in this aspect-by-aspect approach include the risk of misjudgement of impacts and overlooking of better alternative solutions based on taking cross-cutting issues into account (Brown, 1998). Projects appraised in this manner risk failure as their formulation is biased or incomplete. In an ideally integrated SDA approach, different assessments are no longer required, and the project officer would be presented with an integrated overall picture, covering all choices that can be made. Various degrees of integration could be done. For example, procedural tuning of the various sectoral assessments may create sufficient overlap in the timing of assessments so


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that different assessment teams have the opportunity to communicate and exchange findings. Assefa (2005) argues that SDA may be combined with traditional technology assessment (TA) and systems analysis to provide an integrated, holistic approach. Development cooperation has resulted, so far, in less than optimal project quality. Initially, development cooperation targeted only economic and technical goals. As awareness grew, policy themes relating to culture, equity, gender, environment and institutional capacity emerged. An integrated approach would overcome the weaknesses of an aspect-byaspect approach, leading to a more optimal project formulation and that would simplify project decision making. Since the sustainable development goal has independent economic, social and environmental components, it is argued that appraisal procedures and methodologies should use interconnected economic, social and environmental appraisal criteria which are consistent with achieving this goal. There is a clear need to strengthen SDA methods to use at a more strategic level of decision making relating to development policies, plans and programmes (see Section 3.4). Traditional decision making relies heavily on economics. Thus, an initial practical step toward integration would be the systematic incorporation of environmental and social issues into the economic policy framework of human society – e.g. using the ‘issues–policy transformation mapping’ method. Issues–policy transformation mapping Issues–policy transformation mapping (ITM) is a method of integrating and applying various components of SDA (such as EAs and SAs) within the policy process. Figure 2.2 provides an example of how environmental issues are transformed and mapped into

Environmental systems

Decision-making structure

Analytical tools and methods

global

and air

international economical analysis national macroeconomical analysis

national macroeconomical

technoengineering financial analysis

sectoral & subnational analysis project evaluation, cost–benefit analysis

Conventional economic analysis

impact valuation

urban, industrial

Sustainomics environment–economy interface

water

physical, biological and social impacts

land

Environmental assessment

natural habitats

integrated macroeconoglobal resource mical analysis environmental management & environmen- economic tal accounting analysis

international

transnational

sectoral regional

sub-sectoral project

Figure 2.2. Issues–policy transformation mapping to incorporate sustainable development issues into conventional decisions.

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implementable actions and policies in the decision-making domain. The right-hand side of the diagram indicates the hierarchical nature of conventional decision making and implementation in a modern society. The global and transnational level consists of sovereign nation states. In the next level are individual countries, each having a multisector macroeconomy. Various economic sectors (such as industry and agriculture) exist in each country. Finally, each sector consists of different sub-sectors and projects. The usual decision-making process on the right-hand side of the figure relies on technoengineering and financial and economic analyses of projects and policies. In particular, conventional economic analysis has been well developed in the past and uses techniques such as project evaluation/cost–benefit analysis, sectoral/regional studies, multisectoral macroeconomic analysis and international economic analysis (finance, trade, etc.) at the various hierarchic levels. Unfortunately, environmental and social analysis cannot be carried out readily using the above decision-making structure. We examine how environmental issues might be incorporated into this framework (with the understanding that similar arguments may be made with regard to social issues). The left side of Figure 2.2 shows one convenient environmental breakdown in which the issues are: * * * * *

global and transnational (e.g. climate change, ozone layer depletion); natural habitat (e.g. forests and other ecosystems); land (e.g. agricultural zone); water resource (e.g. river basin, aquifer, watershed); and urban–industrial (e.g. metropolitan area, airshed).

In each case, a holistic environmental analysis would seek to study an integrated bio-geophysical system in its entirety. Complications arise when such natural systems cut across the structure of human society. For example, a large and complex forest ecosystem (like the Amazon) could span several countries and also interact with many economic sectors within each country. The causes of environmental degradation arise from human activity (ignoring natural disasters and other events of non-human origin) and, therefore, we begin on the right-hand side of Figure 2.2. The ecological effects of economic decisions must then be traced through to the left-hand side. The techniques of EA have been developed to facilitate this difficult analysis (World Bank, 1998). For example, destruction of a primary moist tropical forest may be caused by hydroelectric dams (energy sector policy), roads (transport sector policy), slash and burn farming (agriculture sector policy), mining of minerals (industrial sector policy), land clearing encouraged by land-tax incentives (fiscal policy) and so on. Disentangling and prioritizing these multiple causes (right-hand side) and their impacts (left-hand side) needs a complex analysis. Figure 2.2 also shows how sustainomics could play its bridging role at the ecology– economy interface by transforming and mapping the EA results (measured in physical or ecological units) onto the framework of conventional economic analysis. A variety of environmental and ecological economic techniques, including valuation of environmental impacts (at the local/project level), integrated resource management (at the sector/regional level), environmental macroeconomic analysis and environmental accounting (at the


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economy-wide level) and global/transnational environmental economic analysis (at the international level), facilitate this process of incorporating environmental issues into traditional policy making. Since there is considerable overlap among the analytical techniques described above, this conceptual categorization should not be interpreted too rigidly. Furthermore, when economic valuation of environmental impacts is difficult, techniques such as multicriteria analysis would be useful (see below). Once the foregoing steps are completed, projects and policies must be redesigned to reduce their environmental impacts and shift the development process toward a more sustainable path. Clearly, the formulation and implementation of such policies is itself a difficult task. In the deforestation example described earlier, protecting this ecosystem is likely to raise problems of coordinating policies in a large number of disparate and (usually) non-cooperating ministries and line institutions (i.e. energy, transport, agriculture, industry, finance, forestry, etc.). Analogous reasoning may be readily applied to SA at the society–economy interface, in order to incorporate social considerations more effectively into the conventional economic decision-making framework. In this case, the left-hand side of Figure 2.2 would include key elements of SA, such as asset distribution, inclusion, cultural considerations, values and institutions. Impacts on human society (i.e. beliefs, values, knowledge and activities) and on the bio-geophysical environment (i.e. both living and non-living resources) are often interlinked via second- and higher-order paths, requiring integrated application of SA and EA. This insight also reflects current thinking on the co-evolution of socioeconomic and ecological systems (see Chapter 4). In the framework of Figure 2.2, the right-hand side represents a variety of institutional mechanisms (ranging from local to global) that would help to implement policies, measures and management practices to achieve a more sustainable outcome. Implementation of sustainable development strategies and good governance would benefit from the transdisciplinary approach advocated in sustainomics. For example, economic theory emphasizes the importance of pricing policy to provide incentives that will influence rational consumer behaviour. However, cases of seemingly irrational or perverse behaviour abound, which might be better understood through findings in areas such as behavioural and social psychology and market research. Such work has identified basic principles that help to influence society and modify human actions, including reciprocity (or repaying favours), behaving consistently, following the lead of others, responding to those we like, obeying legitimate authorities and valuing scarce resources (Cialdini, 2001). Cost–benefit analysis and multicriteria analysis Cost–benefit analysis (CBA) is the main tool for economic and financial assessment. It is a single-valued approach based on neoclassical economics (Box 2.2), which seeks to assign monetary values to the consequences of an economic activity. The resulting costs and benefits are combined into a single decision-making criterion such as the net present value (NPV), the internal rate of return (IRR) or the benefit–cost ratio (BCR). Useful variants include costeffectiveness and least-cost-based methods. Both benefits and costs are defined as the

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difference between what would occur with and without the project being implemented. The economic efficiency viewpoint usually requires that shadow prices (or opportunity costs) be used to measure costs and benefits. All significant impacts and externalities need to be valued as economic benefits and costs. However, since many environmental and social effects may not be easy to value in monetary terms, CBA is useful mainly as a tool to assess economic and financial outcomes. Chapter 3 provides further details. Multicriteria analysis (MCA), or multiobjective decision making, is particularly useful in situations when a single criterion approach like CBA falls short – especially where significant environmental and social impacts cannot be assigned monetary values (see Chapter 3). In MCA, desirable objectives are specified and corresponding attributes or indicators are identified. Unlike in CBA, the actual measurement of indicators does not have to be in monetary terms; i.e. different environmental and social measures may be developed, side by side with economic costs and benefits. Thus, more explicit recognition is given to the fact that a variety of both monetary and non-monetary objectives and indicators may influence policy decisions. MCA provides techniques for comparing and ranking different outcomes, even though a variety of indicators are used. Other specific models and methods The subsequent chapters contain several other methods and models which are specific to particular applications and adapted to the sustainomics approach, including: * * * *

*

*

integrated assessment models (IAMs); macroeconomic models (simulation, growth, computable general equilibrium (CGE), etc.); green accounting (e.g. integrated national economic-environmental accounting or SEEA); sectoral approaches (sustainable energy development (SED), sustainable transport development (STD), sustainable water resources management (SWARM), sustainable hazard reduction and management (SHARM), etc.); shadow pricing and costing methods (economic efficiency, social equity, environmental externalities, separable costs remaining benefits allocation (SCRB), etc.); integrated resource pricing (energy – LRMC-based, water, etc.).

Indicators and measures The practical implementation of sustainomics principles and application of integration tools will require the identification of specific economic, social and environmental indicators that are relevant at different levels of aggregation, ranging from the global/macro to local/micro. It is important that these measures of sustainable development be comprehensive in scope, multidimensional in nature (where appropriate) and account for spatial differences. If we wished to apply the full-cycle analysis approach of sustainomics (see Sections 2.1.3 and 2.1.4) to trace causal linkages, one useful classification of indicators would be by pressure, driver, state, impact and response. For example, consider the following chain (see Chapter 5): underlying pressure – societal values and tastes; immediate driver – greater use of sport utility vehicles (SUVs); state – increased GHG concentrations; impact – global warming; policy response – tax on SUVs and consumer education to encourage more sustainable behaviour.


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A wide variety of indicators are described in the literature (Adriaanse, 1993; Alfsen and Saebo, 1993; Azar, Homberg and Lindgren, 1996; Bergstrom, 1993; Eurostat, 2006; Gilbert and Feenstra, 1994; Holmberg and Karlsson, 1992; Kuik and Verbruggen, 1991; Liverman et al., 1988; Moffat, 1994; Munasinghe and Shearer, 1995; OECD, 1994; Opschoor and Reijnders, 1991; UN, 1996; UNCSD, 2005; UNDP, 1998; World Bank, 1998). We discuss briefly below how measuring economic, environmental (natural), human and social capital raises various problems. In the economic dimension, the word ‘capital’ or ‘asset’ implies stock of wealth to produce economic goods and services. Social and environmental assets have a broader meaning, as discussed below. Manufactured capital may be estimated using conventional neoclassical economic analysis. As described later in the section on cost–benefit analysis, market prices are useful when economic distortions are relatively low, and shadow prices could be applied in cases where market prices are unreliable (see, e.g., Squire and van der Tak, 1975). Natural assets need to be quantified in terms of key biophysical attributes. Typically, damage to natural capital may be assessed by the level of air pollution (e.g. suspended particulates, sulphur dioxide or GHGs), water pollution (e.g. biological-oxygen demand (BOD) or chemical-oxygen demand (COD)) and land degradation (e.g. soil erosion or deforestation). Then the physical damage could be valued using a variety of techniques based on environmental economics (Chapter 3; Freeman, 1993; Munasinghe, 1992a; Tietenberg, 1992). Social capital is the one that is most difficult to assess (Grootaert, 1998). Putnam (1993) described it as ‘horizontal associations’ among people, or social networks and associated behavioural norms and values, which affect the productivity of communities. A somewhat broader view was offered by Coleman (1990), who viewed social capital in terms of social structures, which facilitate the activities of agents in society – this permitted both horizontal and vertical associations (like firms). An even wider definition is implied by the institutional approach espoused by North (1990) and Olson (1982), which includes not only the mainly informal relationships implied by the earlier two views, but also the more formal frameworks provided by governments, political systems, legal and constitutional provisions, etc. Recent work has sought to distinguish between social and political capital (i.e. the networks of power and influence that link individuals and communities to the higher levels of decision making). Human resource stocks may be measured in terms of the value of educational levels, productivity and earning potential of individuals. Chopra (2001) argues that one key measure of social capital especially relevant to development of poor communities is the cooperation between individuals across the traditional divides separating state, market and non-market institutions. Currently, there is no universally accepted aggregate measure of sustainable development to rival economic indicators of welfare such as GDP (whose shortcomings are discussed in Chapters 3 and 7). While many alternative indicators have been suggested by individual researchers, measures proposed by UN organizations are more widely known, including the human development index (UNDP, 2005b), wealth stocks (World Bank, 2006) and environmentally adjusted national accounts (UN, 2003); see Section 3.7.5. The UN

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Commission on Sustainable Development proposes a set of social, economic, environmental and institutional indicators. Data for most nations are available through the ‘Dashboard of Sustainability’ – a versatile and effective tool that allows users to select various sustainable development indicators, aggregate them appropriately and apply them at different geographic scales and for specific years (CGSDI, 2006). This tool also contains the MDG indicators, currently the most important framework for development policy. IISD (2006) provides further information on indicators.

2.5 Restructuring development and growth for greater sustainability A wide range of recent ideas on long-term growth and sustainable development was introduced in Section 1.4. The same theme is pursued further in this section, with a focus on restructuring to make development more sustainable. Growth is a major objective of almost all developing countries – especially the poorest ones. This promise cannot be fulfilled unless economic growth is sustained into the long term. The developing countries need to ensure that their endowments of natural resources are not taken for granted and squandered. If valuable resources such as air, forests, soil and water are not protected, development is unlikely to be sustainable – not just for a few years, but for many decades. Furthermore, on the social side, it is imperative to reduce poverty, create employment, improve human skills and strengthen institutions.

2.5.1 Harmonizing development with nature Let us examine the alternative growth paths available and the role of sustainomics principles in choosing options. Lovelock (1979) made a pioneering contribution with his Gaia hypothesis. He proposed that the totality of life on Earth might be considered an integrated web which works together to create a favourable environment for survival. As a corollary, the unregulated expansion of human activity might threaten the natural balance. In this spirit, Figure 2.3(a) shows how the socioeconomic sub-system or ‘anthroposphere’ (shaded lar so rgy e en . es t. r na ergy en

ed iat rad ergy en

bio-geosphere ste on wa lluti po

small socioeconomic sub-system (anthroposphere)

bio-geosphere

large socioeconomic sub-system (anthroposphere)

ecological services

(a)

(b)

Figure 2.3. Restructuring development to make the embedded socioeconomic sub-system (anthroposphere) more sustainable within the broader bio-geosphere. (a) Unsustainable; (b) sustainable. Source: Munasinghe (1992).


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rectangle) has always been embedded within a broader bio-geophysical system or ‘biogeosphere’ (large oval). National economies are inextricably linked to, and dependent on, natural resources – since everyday goods and services are in fact derived from animate and inanimate resources that originate from the larger bio-geosphere. We extract oil from the ground and timber from trees, and we freely use water and air. At the same time, such activities have continued to expel polluting waste into the environment, quite liberally. The broken line in Figure 2.3(a) symbolically shows that, in many cases, the scale of human activity in the anthroposphere has increased to the point where it is now impinging on the underlying bio-geophysical system (see Chapter 3). This is evident today if we consider that forests are disappearing, water resources are being polluted, soils are being degraded and even the global atmosphere is under threat. Consequently, the critical question involves how human society might contain or manage this problem of scale? One traditional view that has caused confusion among leaders around the world is the assumption that concern for the environment is not necessarily good for economic activity. Thus, until recently, the conventional wisdom held that it was not possible to have economic growth and a good environment at the same time, because they were mutually incompatible goals. However, the more modern viewpoint (embodied also in sustainomics) indicates that growth and environment are indeed complementary. One key underlying assumption is that it is often possible to devise so-called ‘win–win’ policies, which lead to economic as well as environmental gains (Munasinghe et al., 2001). As illustrated in Figure 2.3(a), the traditional approach to development would certainly lead to a situation where the economic system would impinge upon the boundaries of the ecosystem in a harmful manner. On the other hand, Figure 2.3(b) summarizes the modern approach that would allow us to have the same level of prosperity without severely damaging the environment. In this case, the oval outer curve is matched by an oval inner curve – where economic activities have been restructured in a way that is more harmonious with the ecosystem.

2.5.2 Changing the structure of growth Another way of depicting the importance of changing the structure of development and growth is illustrated in Figure 2.4, which shows how environmental risk in a country (e.g. represented by GHG emissions per capita) might vary with its level of development (e.g. measured by GNP per capita). One would expect carbon emissions to rise more rapidly during the early stages of development (along AB) and begin to level off only when per capita incomes are higher (along BC). A typical developing country may be at a point such as B on the curve and an industrialized nation may be at C. Ideally, industrial countries (exceeding safe limits) should increase environmental protection efforts and follow the future growth path CE. Munasinghe (1995a, 1999a) proposed the idea of developing countries adopting policies to ‘tunnel’ through (along BDE) by learning from past experiences of the industrialized world – the tunnel would lie below the safe limit at which environmental damage (such as climate change or biodiversity loss) could become irreversible.

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Framework and fundamentals C environmental risk (e.g. per capita GHG emissions)

safe limit ‘tunnel’ D

E

B

A

development level (e.g. per capita income)

Figure 2.4. Environmental risk versus development level.

Such a tunnel also corresponds to a more economically optimal path and resembles ‘turnpike’ growth paths, which appeared in past literature (Burmeister and Dobell, 1971). The highly peaked path ABCE could result from economic imperfections that make private decisions deviate from socially optimal ones. Corrective policies would help to reduce such divergences and permit movement through the tunnel BDE. Developing countries could thereby avoid severe environmental degradation along conventional development paths of industrial economies (ABCE). This approach is not concerned with the related issue of the existence of the so-called environmental Kuznets curve for any single country or group of nations. Instead, ‘tunnelling’ focuses on identifying policies to delink environmental degradation and economic growth (Munasinghe, 1995a, 1999a; Opschoor 1998b). Chapter 7 describes several ways to find such a policy ‘tunnel’. (1) Actively seek ‘win–win’ policies that simultaneously yield both economically and environmentally (and socially) sustainable paths. (2) Use complementary policies. Growth-inducing economy-wide policies could combine with imperfections in the economy to cause environmental and social harm. Rather than halting economic growth, complementary measures may be used to remove such imperfections and thereby prevent excessive environmental and social harm. Such measures include ex-ante environmental (and social) assessment of projects and policies, introducing remedies that eliminate imperfections (such as policy distortions, market failures and institutional constraints) and strengthening capacity for environmental and social protection. (3) Consider the fine-tuning of growth-inducing economy-wide policies (e.g. altering their timing and sequencing), especially where severe environmental and social damage could occur.

It would be fruitful to encourage a more proactive approach whereby the developing countries could learn from the past experiences of the industrialized world – by adopting sustainable development strategies and climate change measures that would enable them to follow development paths such as BDE in Figure 2.4 (Munasinghe, 1998b). Thus, the


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emphasis is on identifying policies that will help delink carbon emissions and growth, with the curves in Figure 2.4 serving mainly as a useful metaphor or organizing framework for policy analysis. This representation also illustrates the complementarity of the optimal and durable approaches discussed earlier. It has been shown that the higher path ABC in Figure 2.4, could be caused by economic imperfections that make private decisions deviate from socially optimal ones (Munasinghe, 1999a). Thus, the adoption of corrective policies that reduce such divergences from optimality, and thereby reduce GHG emissions per unit of output, would facilitate movement along the lower path, ABD. Concurrently, the durability viewpoint also suggests that flattening the peak of environmental damage (at C) would be especially desirable to avoid exceeding the safe limit or threshold representing dangerous accumulations of GHGs (shaded area). Several authors have econometrically estimated the relationship between GHG emissions and per capita income using cross-country data and found curves with varying shapes and turning points (Cole, Rayner and Bates, 1997; Holtz-Eakin and Selden, 1995; Sengupta, 1996; Unruh and Moomaw, 1998). One reported outcome is an inverted U-shape (called the environmental Kuznet’s curve, or EKC) – like the curve ABCE in Figure 2.4. In this case, the path BDE (both more socially optimal and durable) could be viewed as a sustainable development ‘tunnel’ through the EKC (Munasinghe, 1995a, 1999a). In the above context, it would be fruitful to seek specific interventions that might help to make the crucial change in mindset, where the emphasis would be on the structure of development, rather than the magnitude of growth (conventionally measured). Sustainomics promotes environmentally and socially friendly technologies, which use natural-resource inputs more frugally and efficiently, reduce polluting emissions and facilitate public participation in decision making. Box 2.5 shows how science and technology (S&T) policy may be better integrated into a national sustainable development strategy. One example is information technology (IT), which could make development more sustainable by increasing economic productivity (Munasinghe, 1987, 1989, 1994a). From an environmental perspective, it would make modern economies more services oriented – by shifting activities away from highly polluting and material intensive types of manufacturing and extractive industries. If properly managed, IT might also promote social sustainability, by improving access to information, increasing public participation in decision making and empowering the poor. The correct blend of market forces and regulatory safeguards are required.

2.5.3 Long-term growth and sustainable development We conclude the chapter with some recent ideas about growth and development. The three dimensions of the sustainable development triangle (see Section 2.2), are reflected in contemporary thinking on the fundamental determinants of the developmental status of countries. Some researchers have emphasized the economic engine of trade as the main driver of growth and development (Frankel and Romer, 1999; World Bank, 1993c). Others

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Box 2.5 Science and technology for making development more sustainable Making development more sustainable (MDMS) will require science and technology (S&T) and research methods that are in harmony with the new sustainable development paradigm, human values and social institutions (see Section 1.2). Sustainomics encourages a more holistic, transdisciplinary analysis and solutions. This view is confirmed by findings in basic areas such as quantum physics and complexity theory, as well as applied disciplines such as economics, sociology and ecology, which show that everything is interdependent. Many of our current problems have arisen because we have ignored increasingly important interconnections – given the rapidly growing scale of human activity and consequent impacts on both natural and socioeconomic systems. A new synthesis is needed that combines the dominant Cartesian analytical, reductionist methods of modern science (which have made great advances in knowledge possible) with the more holistic philosophies of the past (which stress interdependence at all levels). Sustainomics seeks to use S&T to address current major world issues and make development more sustainable (see Section 1.2), rather than to reverse progress and go back to some pre-technological state. Ultimately, we wish to make a fundamental long-term transition to a global sustainable society (see Figure 1.1). Worldwide investments in R&D (both public and private) are large and growing. For example, the largest R&D spenders, USA and China, allocated US $330 and 136 billion for this purpose in 2006 (FT, 2006a, 2006b). Meanwhile, Ford and Samsung spent about US $8 and 5.5 billion, respectively, on R&D during 2005 and 2006. Figure B2.2 shows

3.5

role of R&D expenditure to GDP (%)

Finland (2002) Japan (2002)

3 Korea (2003) Germany (2003) Korea (2000) Taiwan (2002) OECD AVG.

2.5

2

USA (2003) France (2002) Singapore (2002)

UK (2002) 1.5

China (2002)

1 0

2

Ireland (2001)

4 6 8 10 12 14 total number of researchers per 1000 employment

16

Figure B2.2. R&D expenditures and number of researchers in selected countries.

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R&D expenditures and the number of researchers in scientifically advanced countries. In some cases, the north–south S&T divide is narrowing, with the growing capabilities and accomplishments of scientists and more effective policies in scientifically advanced developing nations (Hassan, 2005). Typically, China and India invest 1 to 1.5% of GDP on S&T and are emerging as world leaders in key areas. However, there is a disturbing south–south gap emerging between the scientifically proficient countries (e.g. Brazil, China, India) and lagging ones (e.g. Sub-Saharan Africa). It is widely agreed that building S&T capacity is critical to harnessing knowledge for development. S&T innovation may be promoted by strengthening S&T capacity that focuses on (1) solving priority problems; (2) supporting key sectors; and (3) improving decision making (Watkins et al., 2007). Sustainomics provides the framework for such actions. Sustainomics promotes an S&T policy that is better integrated into national sustainable development strategy and objectives. Such a mainstreaming approach enables scientists to make clear to decision makers and senior officials what the key linkages and priorities might be, and how to identify practical options and implement solutions. Ultimately, national policies should not only guide public investments in research and development (especially education and capacity building), but also provide incentives to encourage corresponding activity in the private sector and make effective use of market forces. It would require developing strategic policy tools (such as Action Impact Matrix, AIM) and applying them through multidisciplinary, multistakeholder teamwork and consultations. The AIM methodology (see Section 2.4) has been used to identify and prioritize impacts of investments in key S&T areas (such as agroenergy, bioenergy, information, medical, micro- and nano, technologies and indigeneous sciences and knowledge) on major national sustainable development goals and policies (such as growth, poverty alleviation, food security, employment, health, etc.). A more sophisticated two-stage AIM process is also possible, where the first matrix identifies impacts of S&T on key economic sectors and the second determines effects of sectoral developments on national sustainable development goals and policies (MIND, 2004). The convolution of the two AIMs yields the desired links between S&T areas and sustainable development goals and policies. While sensible public policy interventions could be very beneficial, prudence suggests that such policy should be flexible, encourage innovation and avoid locking-in specific technologies for long periods – because future scientific discoveries and their outcomes are unpredictable. Every innovation that solves one set of problems is likely to create new ones. One example is nuclear technology, which has both peaceful and military uses. Another key example is the race between S&T progress (which improves resource productivity and reduces costs) and problems caused by the greater consumption it stimulates. Almost 150 years ago, Jevons (1865) set out his famous paradox concerning energy use: ‘It is wholly a confusion of ideas to suppose that the economical use of fuel is equivalent to diminished consumption. The very contrary is the truth… every improvement of the engine…accelerates anew the consumption of coal.’ In this

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same vein, at the turn of the nineteenth century, transport experts warned that the streets of London would soon be knee-deep in horse droppings because of the growth of traffic. This issue was resolved with the advent of the ‘horseless carriage’ (motor car) in the early twentieth century. However, rising oil use, traffic jams and urban air pollution from cars again caused pessimism in the post-World War 2 period. In recent decades, mobility management and more energy efficient and less polluting vehicles have eased the problem, and new technologies (such as hydrogen-fuelled cars) offer further hope. This type of cycle will undoubtedly continue, unless we focus more on MDMS.

feel that natural environment, climate and location represented broadly by geography and resource endowments are the dominant influences that explain the difference between development and stagnation (Diamond, 1997; Sachs, 2001). Finally, a third argument has been advanced that social forces are important in explaining wide income variations between rich and poor countries. They emphasize the role of institutions – i.e. how explicit and implicit behavioural norms govern social conduct and ultimately determine economic behavior (Acemoglu et al., 2001; North, 1990). A more integrated viewpoint is provided by the concept of long-term co-evolution of socioeconomic and ecological systems within a more complex adaptive system (see Section 2.3.1). Munasinghe et al. (2001) provide a wide range of current ideas on the complex links between long-term growth and sustainable development by leading researchers in the world. Growth and sustainability Opschoor (2001) explores the negative relationships between economic growth and environmental sustainability, while proposing institutional and moral reforms to promote sustainable development. Norgaard (2001) illustrates some basic problems with rapid growth, discusses some myths concerning economic growth and finally outlines an agenda based on ecological economics to go beyond growth and globalization. Hinterberger and Luks (2001) deal with competitiveness (economic development), employment (social development) and dematerialization (environmental sustainability) in a rapidly globalizing world. A fourth ‘corner’ is added to the sustainable development triangle (institutions – which was embedded within the social dimension in Figure 2.1), forming a pyramid. Ocampo (2001) advocates consolidation of strong institutions for sustainable development in Latin America and the Caribbean, and argues that price reforms are less effective than technical change. General analytical frameworks Daly (2001) shows how traditional marginal analysis in microeconomics, which fails to internalize environmental and social externalities, will lead to overestimation of macroeconomic GNP. Globalization is pushed by powerful transnational corporations to weaken the nation state, leading to uneconomic growth, increased population, greater inequality, increased unemployment and environmental harm. Sachs (2001) seeks to integrate development (economic), human rights (social) and environment. He disputes the usefulness of


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valuing ecosystems, since it may promote unbalanced agreements on intellectual property rights and the unsustainable privatization of all natural capital and ecosystem services. Because ecological economics addresses social issues inadequately, a new discipline is proposed, along the lines of sustainomics. Naredo (2001) argues that even recent valuation methods, such as the pollution analysis, life-cycle analysis and the new System of National Accounts (SNA), are inadequate for sustainable development because they mainly incorporate the monetary values but not the underlying physical information. He proposes a complementary approach that would allow more accurate calculations of the physical cost of recovering mineral resources from the Earth’s crust. Modelling applications Kadekodi and Agarwal (2001) show that the shape of the EKC depends upon the capital intensity of the energy-based natural-resource-using sectors, during the process of economic development (see Section 2.5.2). Factor price changes that favour labour-intensive goods will affect the shape of the curve. Tsigas et al. (2001) use a modified global, applied general equilibrium model to suggest that trade liberalization in the Western Hemisphere coupled with harmonization of environmental policy will benefit all countries, although environmental quality may decline in Mexico and Brazil. Batabyal, Beladi and Lee (2001) explain how developing countries have attempted to improve their balance of payment positions and develop manufacturing industries, by actively following a policy of encouraging importsubstituting industrialization. Brazil, Mexico, Pakistan and the Philippines have used the infant industry argument to apply trade policies that systematically protect the manufacturing sectors. Baer and Templet (2001) use the Greenhouse Limitation Equity Assessment Model (GLEAM) to analyse global climate mitigation policies (see Chapter 5). They conclude that per capita allocations of GHG emissions permits produce the greatest average welfare levels – with feasible emission scenarios that stabilize CO2 at less than twice pre-industrial levels. Hansen (2001) compares the merits of five different methods for estimating the capital consumption of non-renewable resource rents and shows how the discount rate, depletion period and depletion path influence the outcome. Neumayer (2001) criticises the World Bank ‘genuine savings’ method, which appears to show that many Sub-Saharan, North African, Middle Eastern and other countries have failed to pass the test of weak sustainability (see Section 2.3.2). These results are reversed if the alternative El Serafy method is used, with a relatively low discount rate of 4%. The genuine savings concept is unreliable because it depends on a dynamic optimization framework, whereas most economies develop along non-optimal paths.

3 Economics of the environment1

This chapter explores how economics relates to environmental (and related social) concerns. Section 3.1 outlines how environmental degradation is impeding economic development, while human activity is harming the environment. Sections 3.2 and 3.3 expand on economic cost–benefit analysis – a key element of SDA and the project cycle. Important details are explained, including economic decision criteria, efficiency and social shadow pricing, economic imperfections (market failures, policy distortions and institutional constraints), methods of measuring costs and benefits and qualitative considerations. Types of environmental assets and services, and practical techniques of valuing them, are described in Section 3.4. Section 3.5 outlines multicriteria analysis, which is useful for decision making when economic valuation is difficult. Key issues relating to discounting, risk and uncertainty are set out in Section 3.6. Finally, Section 3.7 explains links between economy-wide policies and environmental (and social) issues, as well as environmentally adjusted national accounts. 3.1 Human activities and the environment Mankind’s relationship with the environment has gone through several stages, starting with primitive times, in which human beings lived in a state of symbiosis with nature. Human interactions were primarily within the biotic sphere. This phase was followed by a period of increasing mastery over nature up to the industrial age, in which technology was used to manipulate physical laws governing the abiotic sphere. The outcome was the rapid materialintensive and often unsustainable growth patterns of the twentieth century, which damaged the natural-resource base. The initial reaction to such environmental harm was a reactive approach characterized by increased clean-up activities. Recently, a more proactive attitude has emerged, including the design of projects and policies that will help to make development more sustainable (see Chapter 2). Both environmental and resource economics and ecological economics are useful to address these issues (see Boxes 2.1 and 2.3). They have been defined comprehensively by other authors (e.g. Costanza et al., 1997; Freeman, 1993; Gowdy and Ericson, 2005; Opschoor, Button and Nijkamp, 1999; Tietenberg, 1992; Van den Bergh, 1999). These 1

Some parts of the chapter are based on material adapted from Munasinghe (1992a, 1993a, 1999b, 2002b, 2004b).

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3 Economics of the environment

73

two disciplines overlap (Turner, 1999). Instead of highlighting the differences, we focus on the common elements that support the sustainomics framework. A recent training textbook issued by the World Bank and European Commission provides an excellent review of the subject – starting with sustainomics and the sustainable development triangle (Markandya et al., 2002) The environmental assets that are under threat due to human activities provide three main types of services to society – provisioning, regulation and aesthetic–cultural (details given in Chapter 4). Environmental and ecological economics help us incorporate ecological concerns into the conventional human decision-making framework (see Figure 2.2). More generally, the process for improving policies and projects to make development more sustainable involves: (1) identifying biophysical and social impacts of human activities; (2) estimating the economic value of such impacts; and (3) modifying projects and policies to limit harm. 3.2 Conventional project evaluation A development project involves several steps. The systematic approach used in a typical project cycle includes identification, preparation, appraisal, negotiations and financing, implementation and supervision and post-project audit (see Box 3.1). The economic basis of project evaluation, including cost–benefit analysis and shadow pricing are described in what follows. Practical applications are given in Chapters 11 and 15.

3.2.1 Cost–benefit analysis and economic assessment Cost–benefit analysis (CBA) is the economic assessment component of overall sustainable development assessment (SDA) in the project appraisal stage (see Section 2.4.2). CBA assesses project costs and benefits monetarily. Benefits are defined by gains in human wellbeing. Costs are defined in terms of their opportunity costs, which is the benefit foregone by not using resources in the best available alternative application. SDA also requires us to consider a number of non-economic aspects (including financial, environmental, social, institutional and technical criteria) in project appraisal. In particular, the economic analysis of projects differs from financial analysis. The latter focuses on the money profits derived from the project, using market or financial prices, whereas economic analysis uses shadow prices rather than financial prices. Shadow prices (including valuation of externalities) reflect economic opportunity costs and measure the effect of the project on the efficiency objectives in relation to the whole economy. Criteria commonly used in CBA may be expressed in economic terms (using shadow prices) or financial terms (using market prices) – our emphasis will be on economic rather than financial evaluation. The most basic criterion for accepting a project compares costs and benefits to ensure that the net present value (NPV) of benefits is positive: NPV ¼

T X t¼0

ðBt C t Þ=ð1 þ rÞt ;

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Box 3.1 The project cycle A typical project cycle involves: identification, preparation, appraisal, financing, implementation, supervision and evaluation (World Bank, 2006). Identification – involves the preliminary selection of potential projects that appear to be viable in financial, economic, social and environmental terms, and that conform to national and sectoral development goals. Preparation – lasts up to several years, and includes systematic study of economic, financial, social, environmental, engineering–technical and institutional aspects of the project (including alternative methods for achieving the same objectives). Appraisal – consists of a detailed review that comprehensively evaluates the project, in the context of the national and sectoral strategies, as well as the engineering–technical, institutional, economic, financial, social and environmental issues. Environmental and social assessments are also key elements that may affect the project design and alter the investment decision. The economic evaluation itself involves several well defined stages, including the demand forecast, least-cost alternative, benefit measurement and cost–benefit analysis. Financing – if outside financial assistance is involved, the country and financier negotiate measures required to ensure the success of the project and the conditions for funding (usually included in loan agreements). Implementation and supervision – implementation involves putting into effect in the field all finalized project plans; supervision of the implementation process is carried out through periodic field inspections and progress reports. Ongoing reviews help to update and improve implementation procedures. Evaluation – the final stage, involving an independent project performance audit to measure the project outcome against the original objectives. This analysis can yield valuable information to improve processing of future projects.

where Bt and Ct are the benefits and costs, respectively in year t, r is the discount rate and T is the time horizon. Both benefits and costs are defined as the difference between what would occur with and without project implementation. In economic analysis B, C and r are defined in economic terms and shadow priced using efficiency prices (Munasinghe, 1990a). Alternatively, in financial analysis, B, C and r are defined in financial terms. If projects are to be compared or ranked, the one with the highest (and positive) NPV would be preferred. Suppose NPVi = net present value for project i. Then if NPVI > NPVII, project I is preferred to project II, provided also that the scale of the alternatives is roughly the same. More accurately, the scale and scope of each of the projects under review must be altered so that, at the margin, the last increment of investment yields net benefits that are equal (and greater than zero) for all the projects. Complexities may arise in the analysis of interdependent projects. The internal rate of return (IRR) is another project criterion given by T X t¼0

ðBt C t Þ=ð1 þ IRRÞt ¼ 0:


75

Thus, the IRR is the discount rate which reduces the NPV to zero. The project is acceptable if IRR > r, which in most cases implies NPV > 0 (ignoring projects where multiple roots could occur, because the annual net benefit stream changes sign several times). Problems of interpretation occur if alternative projects have widely differing lifetimes, so that the discount rate plays a critical role. If economic (shadow) prices are used, then the terminology internal economic rate of return (IERR) may be used, while the application of financial (market) prices yields the internal financial rate of return (IFRR). Another frequently used criterion is the benefit–cost ratio (BCR): !, ! T T X X t BCR ¼ Bt =ð1 þ rÞ Ct =ð1 þ rÞt : t¼0

t¼0

If BCR > 1, then NPV > 0 and the project is acceptable. Each of these criteria has its strengths and weaknesses, but the NPV is probably the most useful. It may be used to derive the least-cost rule, when the benefits of two alternative projects are equal (i.e. both serve the same need or demand). Then the comparison of alternatives is simplified, since the benefit streams cancel out. Thus, NPVI NPVII ¼

T X

CII;t CI;t =ð1 þ rÞt :

t¼0

Therefore, NPVI > NPVII if T X t¼0

C II;t =ð1 þ rÞt 4

T X

C I;t =ð1 þ rÞt :

t¼0

In other words, the project with the lower present value of costs is preferred. This is called the least-cost alternative (when benefits are equal). However, even after selecting the leastcost alternative, it is still necessary to ensure that this project has a positive NPV.

3.2.2 Shadow pricing Shadow pricing of economic inputs and outputs is used in project analysis when some idealized assumptions of neoclassical economics are violated in the real world (see Box 2.3). Conceptually, one may capture all the key economic relationships in a comprehensive ‘general equilibrium’ model of the economy. In such a model, the overall national development goal might be embodied in an objective function, such as aggregate consumption. Usually, analysts seek to maximize this consumption subject to constraints, including limits on scarce resources (such as capital, labour and environmental assets), structural distortions in the economy and so on – see the optimality-based approach in Chapter 2. Then, the shadow price of a scarce economic resource is the change in value of the objective function, caused by a marginal change in the availability of that resource. In a mathematical programming macroeconomic model, the optimal values of the dual variables (corresponding to the

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binding resource availability constraints in the primal problem) have dimensions of price, and could be interpreted as shadow prices (Luenberger, 1973). While the general equilibrium approach is conceptually important, it is too cumbersome and data-intensive to use. In practice, partial equilibrium methods are used to evaluate shadow prices of key economic resources in a few sectors or areas (Squire and van der Tak, 1975). Efficiency and social shadow prices Two basic types of shadow prices exist, depending on how sensistive society is to income distribution considerations. Consider the national goal of maximizing the present value of aggregate consumption over a long period. If the consumption of different individuals is added directly, regardless of their income levels, then the resulting shadow prices are efficiency prices because they reflect the pure efficiency of resource allocation. Alternatively, if the consumption of low-income groups needs to be raised, shadow prices may be adjusted by income group to give greater weight to the poor in aggregate consumption. Such prices are called social prices. In practice, such formal weighting schemes are seldom used in project evaluation. Instead, distributional and other social issues are addressed by direct targeting of beneficiaries and similar ad hoc methods. In brief, efficiency shadow prices try to establish the economic values of inputs and outputs, while social shadow prices take account of the fact that the income distribution between different societal groups or regions may be distorted in terms of overall national objectives. Our analysis will place primary emphasis on efficiency shadow pricing. Common property resources and externalities Non-priced inputs and outputs, such as common property resources and externalities (especially those arising from environmental impacts), must be shadow-priced to reflect their economic opportunity costs. Access to common property resources is unrestricted, and thus exploitation tends to occur on a first come, first served basis, often resulting in (unsustainable) overuse. Public goods are environmental resources (e.g. scenic view) that are freely accessible and indivisible (i.e. enjoyment by one individual does not preclude enjoyment by others). These properties lead to ‘free-riding’ – a situation in which one user (either knowingly or unknowingly) uses the resource at a price less than the efficient cost and thereby takes advantage of greater contributions by others (Samuelson, 1954). For example, wastewater discharge taxes may be paid by users of a transnational water source in one nation, while the benefits of cleaner water are shared with users in another country who draw from the same source, but do not pay such taxes. The JDB international symposium involving leading economists (Arrow et al., 1996) highlighted and analysed such problems affecting both local and global communities. Externalities are defined as beneficial or adverse effects imposed on others for which the originator of these effects cannot charge or be charged (Coase, 1960). If a (damaging) externality can be economically valued or shadow-priced, then a charge or tax may be levied on the perpetrator, to compensate for and limit the damage. This is the so-called ‘Pigouvian’ or ‘price-control’ approach to environmental regulation. The basic concepts and techniques


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for economic valuation of environmental impacts underlying this approach are discussed later in this chapter. Unfortunately, many externalities are difficult to measure, not only in physical terms, but also in monetary equivalents (i.e. willingness-to-pay). Quite often therefore, the ‘quantity-control’ approach is taken by imposing regulations and standards expressed in physical measurements only that try to eliminate the perceived external damages (e.g. safe minimum standards for pollution). Especially when environmental pollution is severe and obvious, setting standards could serve as a useful first step to raise consciousness and limit excessive environmental damage, until more accurate valuation studies can be carried out. In such cases, the initial emphasis is on cost-effectiveness (i.e. achieving pollution targets at the lowest cost), rather than valuing the benefits of control measures. For example, quantity controls on air pollution that limit the aggregate emission level may be combined with an initial allocation of emission rights among existing and potential polluters (which collectively do not exceed the total emission limit). This is analogous to defining property rights to an open access resource – in this case, the airshed over a particular region. Next, it would be logical to encourage schemes such as marketable pollution permits (which may be competitively traded among polluters) to achieve an economically efficient redistribution of ‘pollution rights’ within the overall emission limit. However, minimum quantity controls may not be an efficient long-term solution if no attempt is made to compare the marginal costs of compliance with the real benefits provided (i.e. marginal damages avoided) – especially as environmental conditions improve over time. In practice, a mix of price and quantity controls is used to protect the environment (Pearce and Turner, 1990). A mixed system allows the various policy instruments to be adjusted flexibly depending on marginal clean-up costs. Thus, an optimal outcome can be approached even without full information concerning control costs (Baumol and Oates, 1988). Practical considerations Shadow prices are location- and time-specific, and their computation may be tedious. Key elements, such as the numeraire, border-priced conversion factors, shadow wage rates, accounting rate of interest (or discount rate), social shadow prices and distribution weights, are described in the appendix, Section 3.8. Applications to resource pricing policy are given in Chapter 14.

3.3 Measuring costs and benefits In CBA, economic costs and benefits of a project are measured by differences in outcome between two alternative scenarios – with and without the project. This process is explained below for a typical resource – water (see also Chapter 12). The same analysis may be easily generalized to other areas such as energy, agricultures, etc.

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unit price

unit price

PV

PO PV

PN DH

PN A

unit price

B

C (a)

water use

DN G

H

water use (b)

DF

PN

DO J

L

F′

F water use

(c)

Figure 3.1. Effects of a water investment project on water use. (a) Same supply quality: DH = demand for household water; PV = cost of water from old source; PN = cost of water from new supply. (b) New use of water: DN = demand for new uses of water. (c) Higher supply quality: DO = demand for water from old source; DF = demand for water from new supply.

3.3.1 Patterns of resource use Figure 3.1 shows the likely effects on water use when piped water is supplied to an area that had no such service previously available. In practice, the effects of introducing piped water will be felt over a number of years, as users gradually make the necessary investments in water-using appliances to take full advantage of the new water system. There are three main reasons why demand for water will shift because of the development of a water supply system (see also Section 14.7): * * *

cost difference between the new supply and the old supply (price shift); consumers find new uses of water, unrelated to any shift in price (greater availability and quantity); consumers switch to a more acceptable source (improved quality).

The first demand effect is illustrated in Figure 3.1(a). It indicates the demand for household water where the new water supply (e.g. pipeborne supply) can substitute for another source of water that was previously used (e.g. water vendor), with little significant change in quality of the useful output. The horizontal axis represents water consumed per unit time, while the vertical axis shows the effective total cost per unit to the customer. Since piped water is usually much cheaper than water from a vendor, consumption will increase from AB to AC. The second demand effect, shown in Figure 3.1(b), arises from new uses of water (e.g. watering a vegetable garden) that were previously not thought of, or considered infeasible, because of the limited quantity available or prohibitively high costs. Thus, the consumption GH represents an entirely new or induced market for water. The third demand effect is shown in Figure 3.1(c). Here, new piped water also displaces an old source, such as contaminated surface water. There is an improvement in quality, which results in the demand curve shifting out from DO to DF. If there was no such shift, demand would have increased from JL to JF′ because of the lower price of water, but, with the additional displacement of the demand curve, the overall consumption would be JF (see Chapter 14).


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unit price

R

E MCA A

PA L

F

G

S

H

I

MC N P

DS D

DA

K QA

O

J Q

water used per month

Figure 3.2. Measuring the net costs and benefits of water use.

3.3.2 Basic economics of cost and benefit measurement Consider Figure 3.2, which is a static picture of the likely water use by a typical consumer, both with and without the project. This case is similar to the one shown in Figure 3.1(c). The symbols are given in the following. Without project condition DA = demand curve for an alternative source of water; QA = quantity of alternative water consumed, in litres per month of water required to produce the equivalent output;

MCA = marginal cost of supplying alternative water; PA = price of alternative water (subsidized below MC). With project condition D = demand curve for water, shifted outward due to higher quality of piped water provided; Q = quantity of piped water consumed, in litres per month; MC = marginal cost of supplying piped water; P = price of piped water (subsidized below MC).

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The benefit of consuming water is given by the area under the demand curve. Therefore, in the ‘without project’ situation, [OAGK] is the user benefit of consuming an amount of water QA, where the string of capitals in brackets indicates the boundary of the area. The corresponding cost of supplying this water is MCA · QA. In the same way, the benefit and cost in the ‘with project’ condition are [OEIJ] and MC · Q, respectively. The project’s incremental benefit (or change in benefit) is given by IB ¼ ½OEIJ ½OAGK ¼ ½AEFG þ ½FHI þ PðQ QA Þ: Similarly, the incremental cost is given by IC ¼ MC Q MC A QA : Finally, the net benefit due to the water supply project is given by NB ¼ IB IC ¼ fPðQ QA Þ þ MC A QA þ½FHI þ ½AEFGg ½MC Q: The final term above indicates the project costs, and we may write this as follows: C ¼ ½MC Q: The remaining part of the expression is usually called the project benefit: B ¼ fPðQ QA ÞÞ þ MC A QA þ½FHI þ ½AEFGg: In the expression for C, the marginal cost element MC is the long-run marginal cost (LRMC) per unit of water supplied. The LRMC is the incremental system cost of supplying one unit of sustained future water consumption (see Chapter 14); Q is the total quantity of new water supplied. The expression for B is more complicated. The first term is the sales revenue corresponding to additional water used, while the second is the cost saving due to alternative water not used. The final two terms are areas representing consumer surplus. In general, these demand curves will shift and consumption levels (as well as the LRMC) will change over time. The present value of the stream of (shadow-priced) net benefits must be evaluated, year by year, over the lifetime of the project, to calculate the NPV and other cost–benefit criteria described earlier.

3.3.3 Estimation of project costs and benefits Total cost The total cost of the new water supply system is given by the least-cost solution. Alternatively, we may use the equations MC = LRMC per unit of water supplied and Q = total quantity of new water. First benefit term: P (Q – QA) The benefit component involving revenues from incremental consumption is the price times the quantity (from the demand forecast). When there is uncertainty concerning future price


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trends, the ‘neutral’ assumption of the constant real future price of water may be used. If this water supply price is well below the level of the LRMC, then the consumer surplus portion of benefits [FHI] will be relatively large and its estimation becomes more important, as discussed below. On the other hand, in the event that price is not very different from the LRMC, then the incremental revenues will approximate the full benefits more closely. Revenues are evaluated in market prices; they must be converted into shadow-priced values (see Section 3.2.4). Second benefit term: MCA · QA The second term in the expression for B represents cost savings from not using water derived from previous sources, measured in shadow prices. The rate at which this substitution takes place has to be predicted and also reflected consistently in the demand forecast. Additional cost-saving benefits may arise due to substitution of hypothetical new water sources that might have emerged in the absence of the water supply project, but these benefits must be carefully justified. Third and fourth benefit terms: [FHI] and [AEFG] The third term in the benefit expression, [FHI], is the consumer surplus associated with incremental water consumed. Additional output due to increased productivity in new activities may be used to approximate some of this willingness-to-pay for water. For example, the availability of more water for irrigation might increase farm yields significantly. The shadow-priced economic value of additional output, net of all input costs including expenditures on water, is the appropriate measure of consumer surplus to be used. Similarly, higher net output derived by replacing an existing water source may be used to estimate consumer surplus [AEFG]. The benefit [FHI] is over and above the cost-saving benefit arising from the replacement of alternative water described earlier.

3.3.4 Benefits that are difficult to value monetarily Non-monetary gains are difficult to value. Analysts must be careful to avoid using such supposed benefits to justify a water supply project that otherwise may not have been viable. Such benefits may be included in the analysis through qualitative judgement. First, improved water supply supports and stimulates modernization and growth. Most of the productivity gains by households, agriculture and industry may be quantified as shown earlier. However, if water supply acts as a catalyst, there may be further unrecognized benefits, for example due to changes in attitudes of the entire community. Second, social benefits could accrue due to overall improvements in the quality of life. For example, clean and accessible water would improve health and sanitation and free up people’s time. Other intangible benefits might include increased personal satisfaction, family welfare and reduced social discontent and unrest.

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Third, water supply may be viewed by governments as a tool for improving social equity and income distribution (Munasinghe, 1988). Often, the benefits of water supply may accrue mainly to the rich. Weighting benefits to favour the poor is problematic because it is difficult to identify poverty groups and determine the correct social weights. Therefore, targeting the benefits of water supply, especially through connections policy and price subsidies, is often a more practical method. Fourth, there may be significant employment and other gains as a result of the water project. The direct employment effects due to greater productive uses of water will be captured by analysing incremental output, as described earlier. In the case of rural water supply, another benefit is reduced rural to urban migration, due to better opportunities for employment and advancement, or improvements in the quality of life. Fifth, it is sometimes argued that better water supply may provide a number of other benefits, from the broad national viewpoint, such as improved political stability, national cohesion and reduced urban–rural and interregional tensions and inequalities. In Figure 3.2, the ‘social’ demand curve DS captures the social surplus benefits or willingness-to-pay of society [ERSI], not directly internalized within demand curves of individual users.

3.4 Basic concepts for valuing environmental costs and benefits This section describes methods of valuing environmental impacts. Little and Mirrlees (1990) noted that from the mid 1970s to the 1990s, there had been a rise and decline of project appraisal in development community. Our view is that natural-resource and environmental issues may be critical for making development more sustainable. Therefore, environmental economic analysis should be pursued, preferably early in the project cycle. Even where the valuation is difficult, techniques like multicriteria analysis are useful to make decisions (see Section 3.5). The first step in the analysis is to determine the environmental (and social) impacts of the project or policy, by comparing the ‘with project’ and the ‘without project’ scenarios (see Section 3.3). Transdisciplinary work is essential (see Section 2.1). The quantification of impacts in non-monetary units is a prerequisite, not only for accurate economic valuation, but also for the use of other analytical methods such as multicriteria analysis. Such biophysical impacts are themselves complex and often poorly understood. The second step in considering environmental effects involves valuing project impacts. Several practical valuation techniques are described below, based on extensions of the framework of Section 3.3.

3.4.1 Categories of economic value Conceptually, the total economic value (TEV) of a resource consists of its (i) use value (UV) and (ii) non-use value (NUV). Use values may be broken down further into the direct use


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total economic value use value

direct use values

indirect use values

non-use value

option values

existence values

outputs that can be consumed directly

functional benefits

future direct and indirect use values

value from knowledge of continued existence

– food – biomass – recreation – health

– ecological functions – flood control – storm protection

– biodiversity – conserved habitats

– habitats – endangered species

other non-use values

decreasing tangibility of value to individuals Figure 3.3. Categories of economic values attributed to environmental assets (examples from a forest).

value (DUV), the indirect use value (IUV) and the option value (OV) (potential use value). One needs to be careful not to count both the value of indirect supporting functions and the value of the resulting direct use. We may write the following: TEV ¼ UV þ NUV or TEV ¼ ½DUV þ IUV þ OV þ ½NUV: Figure 3.3 shows this disaggregation of the TEV in schematic form. A short description of each valuation concept, and a few typical examples of the underlying environmental resources, are provided: * *

*

*

direct use value is the contribution to current production/consumption; indirect use value includes benefits from functional services that the environment provides to support current production/consumption (e.g. ecological functions such as nutrient recycling); option value is the willingness-to-pay for an unutilized asset, simply to avoid the risk of not having it available in the future (see Section 3.6.2); and non-use value is the willingness-to-pay for perceived benefits not related to use value, e.g. existence value, which is based on the satisfaction of merely knowing that an asset exists, even without intending to use it.

Economic theory clearly defines the TUV, but there is considerable overlap and ambiguity in the breakdown categories, especially with regard to non-use values. Thus, option

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values and non-use values are shaded in Figure 3.3. These categories are useful as an indicative guide, but the goal of practical estimation is to measure the TUV rather than its components. The distinction between use and non-use values is not always clear. The latter tend to be linked to more altruistic motives. Differing forms of altruism include: intergenerational altruism, or the bequest motive; interpersonal altruism, or the gift motive; stewardship (which has more ethical than utilitarian origins); and q-altruism, which states that the resource has an intrinsic right to exist. This final definition is outside conventional economic theory and incorporates the notion that the welfare function should be derived from something more than purely human utility (Quiggin, 1991). For the practitioner, the precise conceptual basis of economic value is less important than the various empirical techniques that permit us to estimate a monetary value for environmental assets.

3.4.2 Practical valuation techniques The economic concept underlying all valuation methods is the willingness-to-pay (WTP) of individuals for an environmental service or resource, which is itself based on the area under the demand curve (Freeman, 1993). In Figure 3.4, IHFD0 is the demand curve for an environmental good (e.g. litres per day of water used); AJFS is the supply curve or marginal cost (MC) for each unit supplied. The demand curve is generally downward sloping because each succeeding unit consumed has less value. However, we might expect MC to increase (e.g. as water sources become scarcer and less accessible). At any price p1, the quantity demanded is Q1 and the total economic

value

M I G

p1

S H N

p2 F

p0

supply curve (marginal cost, MC)

B

(price)

demand curves J

D1 D0

A L O

Q1

K Q0 Q2 (quantity)

Figure 3.4. Economic value of an environmental good.

demand


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benefit of consumption is the WTP represented by the area OIHL (mathematically, ∫ p dQ). The corresponding total cost of supply is area OAJL (i.e. ∫ MC dQ). The net benefit (NB) of water use is given by benefit – cost = area AIHJ, which is the economic surplus (or net value) from this activity. NB has two components: areas IHG (consumer surplus) and AGHJ (producer surplus). Net benefits (AIF) are maximized at point F, when the optimal price price p0 is set equal to marginal cost MC and the optimal quantity Q0 is used. Next, we examine how a change in quality of the same environmental good might affect its value. Suppose the curve D0 indicates the demand for an environmental resource in its original condition (e.g. polluted river water). The point I represents the choke price, at which demand falls to zero. Suppose the water quality is improved by environmental clean-up activity. Then the demand curve shifts upward to the new position D1. With the new price and quantity combination (p2, Q2), the new net benefit increases to AMN. Therefore, there is an incremental increase in net value given by the area IFNM, due to the water quality improvement – provided water and water quality are weak complements (Maler, 1974). Theoretically, the compensated or Hicksian demand function should be used to estimate value, since it indicates how demand varies with price while keeping the user’s utility level constant. The change in value of an environmental asset could also be defined by the difference between the values of two expenditure (or cost) functions. The latter are the minimum amounts required to achieve a given level of household utility or firm output, before and after varying the quality of, price of, or access to the environmental resource, while keeping all other aspects constant. Measurement problems arise because the commonly estimated demand function is the Marshallian one – which indicates how demand varies with the price of an environmental good, while keeping the user’s income level constant. In practice, it has been shown that the Marshallian and Hicksian estimates of the WTP are in good agreement for a variety of conditions, and in a few cases the Hicksian function may be derived from the estimated Marshallian demand functions (Braden and Kolstad, 1991; Willig, 1976). People’s willingness-to-accept (WTA) in the way of compensation for environmental damage is another measure of economic value that is related to the WTP; the WTA and the WTP could diverge as discussed below (Cropper and Oates, 1992). In practice, both measures are used in the valuation techniques described below. Empirical evidence indicates that WTP questions yield higher answers than WTA questions about people’s willingness-to-pay to retain the same amenity. Some argue that WTA questions need more time to be understood properly and assimilated, and that the gap between WTA and WTP narrows with successive iterations. Others suggest that people are less willing to pay actual income than to receive ‘hypothetical’ compensation (Knetsch and Sinden, 1984). It may also be the case that individuals are more cautious when weighing the net benefits of changing assets than when no change is made. Generally, WTP is considered to be more consistent and credible a measure than WTA. However, when significant discrepancies exist between the two measures, then the higher values may be more appropriate when valuing environmental losses.

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Framework and fundamentals Type of market Behaviour type

Conventional market Implicit market

Actual behaviour effect on production

travel cost

Constructed market artificial market

wage differences effect on health

property values

defensive or preventive costs

proxy/marketed goods benefit transfer

Intended behaviour

replacement cost shadow project

contingent valuation

Figure 3.5. Techniques for economically valuing environmental impact.

In developing countries, the ability to pay is a concern. In low-income areas, money values placed on environmental goods and services are traditionally low, and income weights may be used (see Section 3.2.2). Alternatively, other social and ethical measures might be used to protect the poor (see Section 13.2.3). Practical valuation methods are categorized in Figure 3.5.

3.4.3 Direct effects valued on conventional markets The methods considered in this section are directly based on changes in market prices or productivity due to environmental impacts. Change in productivity Projects can affect production. Changes in marketed output can be valued by using standard economic prices. Loss of earnings Environmental quality affects human health. Ideally, the monetary value of health impacts should be determined by the WTP for improved health. In practice, proxy measures such as foregone net earnings may be used in case of premature death, sickness or absenteeism (and higher medical expenditures, which can be considered a type of replacement cost). One may avoid ethical controversies, associated with valuing a single specific life, by costing the statistical probability of ill health or death (like the actuarial values used by life insurance firms). Actual defensive or preventive expenditures Individuals, firms and governments undertake ‘defensive expenditures’ to avoid or reduce unwanted environmental effects. Defensive expenditures may be easier to obtain than direct


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valuations of environmental harm. Such actual expenditures indicate that individuals, firms or governments judge the resultant benefits to exceed the costs. Defensive expenditures can then be interpreted as a minimum valuation of benefits.

3.4.4 Potential expenditure valued on conventional markets Replacement cost In this section, the costs to be incurred in order to replace a damaged asset are estimated. The actual damage costs may be higher or lower than the replacement cost. However, it is an appropriate method if there are compelling reasons for restoring the damage. This approach is especially relevant if there is a sustainability constraint that requires certain assets stocks to be maintained intact (see Chapter 2). Shadow project This approach is based on costing one or more ‘shadow projects’ that provide for substitute environmental services to compensate for environmental assets lost under the ongoing project. Further, this approach is often an institutional judgement of replacement cost, and its application would be most relevant when ‘critical’ environmental assets at risk need to be maintained.

3.4.5 Valuation using implicit (or surrogate) markets The techniques described in this section use market information indirectly. Each method has advantages and disadvantages, including specific data and resource needs. Travel cost The travel cost method has been used to measure benefits produced by recreation sites. It determines the demand for a site (e.g. number of visits per year) as a function of variables such as consumer income, price and various socioeconomic characteristics. The price is usually the sum of observed cost elements such as (a) entry price to the site, (b) costs of travelling to the site and (c) foregone earnings or opportunity cost of time spent. The consumer surplus associated with the estimated demand curve provides a measure of the value of the recreational site in question. More sophisticated versions include comparisons across sites, where environmental quality is also included as a variable that affects demand. Property value This is a hedonic price technique based on the more general land value approach, which decomposes real estate prices into components attributable to different characteristics such as proximity to schools, shops, parks, etc. The method seeks to determine the increased WTP for improved local environmental quality, as reflected in housing prices in cleaner surroundings. It assumes a competitive housing market, and its demands on information and tools of statistical analysis are high.

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Wage differential This method is also a hedonic technique, which assumes a competitive market, where the demand for labour equals the value of the marginal product, and labour supply varies with working and living conditions. Thus, a higher wage is necessary to attract workers to locate in polluted areas or undertake more risky occupations. This method relies on private valuation of health risks, not necessarily social ones. Data on occupational hazards must be good for private individuals to make meaningful trade-offs between health risks and remuneration. Finally, the effects of other factors, such as skill level, job responsibility, etc., that might influence wages must be eliminated to isolate the impacts of environment. Marketed goods as proxies for non-marketed goods In situations where environmental goods have close substitutes that are marketed, the value of an environmental good may be approximated by the observed market price of its substitutes. Benefit transfer Values determined at one place and time are used to infer values of similar goods at another place and time (where direct valuation is difficult), with adjustments for differences in incomes, prices, quality, behaviour, etc. (ADB, 1996; Ecological Economics, 2006).

3.4.6 Valuation using constructed markets Contingent valuation When market prices do not exist, this method basically asks people what they are willing to pay for a benefit and/or what they are willing to accept by way of compensation to tolerate a cost. This process of asking may be either through a direct questionnaire/survey, or by experimental techniques in which subjects respond to stimuli in ‘laboratory’ conditions. The contingent valuation method has certain shortcomings, including problems of designing, implementing and interpreting questions. However, in some cases, it may be the only available technique for estimating benefits. It has been applied to common property resources, amenity resources with scenic, ecological or other characteristics and to other situations where market information is not available. Caution should be exercised in seeking to pursue some of the more abstract benefits of environmental assets, such as existence value. Artificial market Such markets could be constructed for experimental purposes to determine consumer willingness-to-pay for a good or service. For example, a home water purification kit might be marketed at various price levels, or access to a game reserve might be offered on the basis of different admission fees, thereby providing an estimate of the value placed on water purity or on the use of a recreational facility, respectively.


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3.5 Multicriteria analysis Projects, policies and their impacts are embedded in a system of broader (national) objectives. If the impacts of projects and policies on these broader objectives can be valued economically, all such effects may be incorporated into the conventional decision-making framework of cost–benefit analysis. However, some social and biophysical impacts cannot be easily quantified in monetary terms, and multicriteria analysis offers a complementary approach that facilitates decision making. Multicriteria analysis (MCA) or multiobjective decision making differs from CBA in three major areas. While CBA focuses on efficiency (although incorporation of income distribution objectives may be attempted), MCA does not impose limits on the forms of criteria, allowing for consideration of social and other forms of equity. Second, while CBA requires that effects be measured in quantitative terms, to allow for the application of prices, MCA can be broken down into three groups: one that requires quantitative data; a second that uses only qualitative data; and a third that handles both simultaneously. Finally, MCA does not require the use of prices, although they might be used to arrive at a score. CBA uses prices which may sometimes be adjusted according to equity weighting. MCA uses weighting involving relative priorities of different groups as opposed to pricing. If efficiency is the only criterion, and prices are available to value efficiency attributes, CBA is preferable. However, in many cases, a paucity of data and the need to incorporate social and biophysical impacts make the use of MCA a more practicable and realistic option. MCA calls for desirable objectives to be specified. These often exhibit a hierarchical structure. The highest level represents the broad overall objectives (e.g. improving the quality of life), which are often vaguely stated and, hence, not very operational. They may be broken down into more operational lower-level objectives (e.g. increased income) so that the extent to which the latter are met may be practically assessed. Sometimes only proxies are available (e.g. if the objective is to enhance recreation opportunities, the number of recreation days can be used). Although value judgements may be required in choosing the proper attribute, measurement does not have to be in monetary terms (like the singlecriterion CBA). More explicit recognition is given to the fact that a variety of concerns may be associated with planning decisions. An intuitive understanding of the fundamentals of MCA can be provided by a twodimensional graphical exposition, such as in Figure 3.6. Assume that a scheme has two non-commensurable and conflicting objectives, Z1 and Z2. For example, Z1 could be the additional project cost required to protect biodiversity and Z2 could be some index indicating the loss of biodiversity. Assume further that alternative projects or solutions to the problem (A, B and C) have been identified. Clearly, point B is superior to (or dominates) A in terms of both Z1 and Z2 because B exhibits lower costs as well as biodiversity loss relative to A. Thus, alternative A may be discarded. However, we cannot make such a simple choice between solutions B and C since the former is better than the latter with respect to objective Z1 but worse with respect to Z2. In general, more points (or solutions) such as B and C may be

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Framework and fundamentals high trade-off curve

equi-preference curves

C CMAX

economic cost

D

A

feasible set of options

O

B

biodiversity loss

BMAX

high

Figure 3.6. Simple multicriteria analysis.

identified to define the set of all non-dominated feasible solution points that form an optimal trade-off curve or curve of best options. For an unconstrained problem, further ranking of alternatives cannot be conducted without the introduction of value judgements. Specific information has to be elicited from the decision maker to determine the most preferred solution. In its most complete form, such information may be summarized by a family of equi-preference curves that indicate the way in which the decision maker or society trades off one objective against the other – typical equi-preference curves are shown in Figure 3.6. The preferred alternative is the one that yields the greatest utility, which occurs (for continuous decision variables as shown here) at the point of tangency D of the best equi-preference curve with the trade-off curve. Since the equi-preference curves are usually not known, other practical techniques have been developed to narrow down the set of feasible choices on the trade-off curve. One approach uses limits on objectives or ‘exclusionary screening’. For example, in the figure the decision maker may face an upper bound on costs, CMAX (i.e. a budgetary constraint). Similarly, ecological experts might set a maximum value of biodiversity loss, BMAX (e.g. a level beyond which the ecosystem collapses). These two constraints define a more restricted portion of the trade-off curve (darker line), thereby reducing and simplifying the choices available. Pearce and Turner (1990) describe five main forms of multicriteria evaluation methods: aggregation, lexicographic, graphical, consensus- maximizing and concordance. Among the various types of MCA, the most suitable method depends upon the nature of the decision situation (Petry, 1990). For instance, interactive involvement of the decision maker has proved useful for problems characterized by a large number of decision variables and complex causal interrelationships. Some objectives may be directly optimized, while others


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will need to meet a certain standard (e.g. level of biological oxygen demand (BOD) not below 5 mg/litre). The major accomplishment of MCA models is that they allow for more accurate representation of decision problems, by accounting for several objectives. However, a key question concerns whose preferences are to be considered. The model only aids a single decision maker (or a homogeneous group). Various stakeholders will assign different priorities to the respective objectives, and it may not be possible to determine a single best solution via the multiobjective model. Also, the mathematical framework imposes constraints upon the ability to represent the planning problem effectively. Non-linear, stochastic and dynamic formulations can assist in better defining the problem, but impose costs in terms of complexity in formulation and solving the model (Cocklin, 1989). In constructing the model, the analyst communicates information about the nature of the problem by specifying why factors are important and how they interact. There is value to be gained in constructing models from differing perspectives and comparing the results. MCA, used in conjunction with a variety of models, and effective stakeholder consultations, could help to reconcile the differences between individual versus social and selfish versus altruistic preferences. In addition to facilitating specific trade-off decisions at the project level, MCA could also help in selecting strategic development paths. 3.6 Discount rate, risk and uncertainty In this section, some key issues that arise in the sustainable development assessment of projects and policies are briefly reviewed.

3.6.1 Discounting and intergenerational choices Discounting is the process by which costs and benefits that occur in different time periods may be compared. It has been a general problem in cost–benefit analysis and is particularly important with regard to long-term environmental issues (Harberger, 1976; Marglin, 1963). In standard analysis, past costs and benefits are treated as ‘sunk’ and are ignored in decisions about the present and future. Future costs and benefits are discounted to their equivalent present value and then compared. In theory the interest rate in a perfect market reflects both the subjective rate of time preference (of private individuals) and the rate of productivity of capital. These rates are equated at the margin by the market, so that the rate at which individuals are willing to trade present for future values is just equal at the margin to the rate at which they are able to transform present goods, in the form of foregone consumption, into future goods (through capital investment). Often, the rate of time preference and the rate of capital productivity are not equal, because of imperfect financial markets and government distortions introduced by taxation. Also, individual decisions differ from social decisions in that individuals are relatively short-lived, whereas societies persist for longer periods. The community usually discounts the future less than individuals. These considerations give rise to the concept of social rate of discount (Box 3.2).

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Box 3.2 Social rate of discount and long-term concerns Social rate of discount The social rate of discount (SRD) is appropriate for determining public policy. Basic issues of value and equity are involved in the choice of such a social discount rate. Sustainable development provides a broad guideline – each generation has the right to inherit economic, social and environmental assets that are at least as good as the those enjoyed by the preceding generation (see Chapter 2). Even in traditional CBA used in project evaluation, the choice of discount rates is not clear cut (Munasinghe, 1992a). They vary across countries, depending on behavioural preferences and economic conditions. Furthermore, it is considered prudent to test the sensitivity of project results by using a range of discount rates (usually about 4 to 12% per annum), even within one country. Starting from the theoretically ideal (or first best) situation of perfectly functioning, competitive markets and an optimal distribution of income (see Box 2.3), it is possible to show that the discount rate should be equal to the marginal returns to investment (MRI), which will also equal the interest rate on borrowing by both consumers and producers (Lind, 1982). There are three conditions to ensure an efficient (or optimal) growth path. First, the marginal returns to investment between one period and the next should equal the rate of interest (i) charged from borrowing producers. Second, the rate of change of the marginal utility of consumption (or satisfaction derived from one extra unit consumed) from one period to the next should be equal to the interest rate (r) paid out to lending consumers. Third, and finally, the producer and consumer rates of interest are equal (i.e. i = r) throughout the economy and over all time periods. As we deviate from ideal market conditions and the optimal income distribution, the choice of discount (or interest) rates becomes less clear. For example, taxes (subsidies) may increase (decrease) the borrowing rate to producers above (below) the interest rate paid to consumers on their savings (i.e. i differs from r). More generally, if the three conditions do not hold because of economic distortions, then efficiency may require project-specific discount rates with corrections to compensate for the economic imperfections. In some cases, no theoretical basis exists to link market interest rates to the social discount rate, but market behaviour could still provide useful data to estimate the latter.

Declining or negative discount rates (in the long term) Traditional discount rate analysis may be used to derive declining (and even negative) discount rates for evaluating costs and benefits over very long (or multigenerational) time periods, when welfare and returns on investment may be falling. Consider the consumer rate of time preference (CTP), which is the subjective discount rate of individuals (as opposed to the MRI, which is market-derived). It has several components:


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CTP = α + βg. Here, α represents the preference of an individual for consumption today rather than in the future – it may be based on the myopic notion of ‘pure’ preference, as well as the risk perception that future consumption may never be realized; β is the elasticity of marginal welfare; and g is the growth rate of consumption. Assuming that welfare (W) depends on consumption (c), we may write W = W(c). Then, by definition, 2 cðd W=dc2 Þ ¼ ðdW=dcÞ and g¼

ðdc=dtÞ : c

Marginal welfare increases with consumption, (dW/dc) > 0, but at a declining rate, (d2W/dc2) < 0, as consumers become satiated. Therefore β > 0, so that the sign of the term (βg) is the same as sign of g. The term (βg) shows that the declining marginal welfare of consumption combined with higher expected future consumption will make the latter less valuable than present-day consumption; i.e. since we are likely to be richer in the future, consumption today is more valuable. The general consensus is that α is close to zero, usually 0–3%, and β may be in the range of 1 to 2. Thus, if g is large (i.e. high expected economic growth rates), then the CTP could be quite large too. On the other hand, if we consider a long-range scenario, in which growth and consumption are falling (e.g. catastrophic global warming in 100 years), then g could become negative and consequently the CTP may be small or even negative. In this case, with the CTP as the discount rate, future costs and benefits would loom much larger in present-value terms than if the conventional opportunity cost of capital (say 8%) were used, thereby giving a larger weight to long-term, intergenerational concerns. The key point is that it may be misleading to choose discount rates without assuming some consistent future scenario; Uzawa (1969) shows how discount rates may be endogenized to reflect future consumption. Thus an optimistic future would favour higher discount rates than a gloomy one, which is consistent, since the risk of future catastrophes should encourage greater concern for the future. Hansen (2006) and Winkler (2006) further discuss the pros and cons of declining (hyperbolic) discount rates. Source: Munasinghe (1992a).

The rate of productivity is higher in many developing countries, because of capital scarcity. In poor countries, the rate of time preference may also be elevated, because of the urgency of satisfying immediate basic needs rather than ensuring long-term sustainability. The neoclassical discounted utility model implies that the rate of time preference is independent of time frames and the amounts of commodities – this is not always true. Furthermore,

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the lack of properly developed capital markets in many developing economies often causes investment decisions to be linked to consumption and to depend on preferences. Higher discount rates may discriminate against future generations. This is because projects with social costs occurring in the long term, and net social benefits occurring in the near term, will be favoured by higher discount rates. Projects with benefits accruing in the long run will be less likely to be undertaken under high discount rates. Thus, future generations will suffer from market discount rates determined by high rates of current generation time preference and/or productivity of capital. The foregoing arguments suggest that discount rates could be lowered to reflect long-term environmental concerns and issues of intergenerational equity – see Section 5.2.3 for a discussion relating to climate change. Yet, this may lead to a problem. Although ecologically sound activities would pass the cost–benefit test more frequently, many more projects would also generally pass the test, and the resulting increase in investment could lead to additional environmental stress (Krautkraemer, 1988). Many environmentalists believe that a zero discount rate should be employed to protect future generations. However, employing a zero discount rate is inequitable, since it would imply a policy of high current sacrifice, which would discriminate against the poor of today. Non-constant (and declining) discount rates may be more relevant to deal with long-term multigenerational issues (see Section 5.2.3), especially where the future productivity of capital is expected to decrease. The discount rate could be determined on a country-specific basis, and be regularly updated, as is the case with other shadow prices. Arbitrary manipulation of discount rates to facilitate intergenerational transfers could distort resource allocations. A better alternative might be to impose sustainability constraints to ensure that the overall stock of capital is preserved or enhanced for future generations (see Chapter 2). Even simple rules that limit specific environmental impacts (e.g. pollution standards) may be a useful first step. Another alternative is to ensure that irreplaceable environmental assets command a premium value in CBA. In summary, the following practical guidance is useful within the context of sustainomics. (a) The standard opportunity cost of capital (e.g. 4–12%) may be used as a benchmark for net present value calculations and as the comparator when the internal rate of return (IRR) is computed. (b) Efforts should be made to ensure that compensating investments offset capital stock degradation within a framework of policy and project decisions. (c) In the case of projects leading to irreversible damage, the CBA should be adapted, to the extent possible, to include a measurement of the foregone benefits of preservation in the computation of costs. (d) Where valuation of environmental and social impacts is difficult, and large irreversible damage might occur, restrictions might be set to limit the damage within acceptable biophysical or social norms. (e) Declining or negative discount rates may be considered for pessimistic long-term scenarios.

3.6.2 Risk and uncertainty problems All projects and policies entail risk and uncertainty. Risks are usually measured by the probabilities assigned to the likelihood of occurrence of an undesirable event (e.g. a natural


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disaster). Uncertainty describes a situation where little is known about future impacts. Therefore, no probabilities can be assigned because the outcomes are undefined. Risk can be treated probabilistically on the basis of estimated data, and therefore it may be insured against and treated like any other project cost. However, uncertainty defies actuarial principles because the future is undefined. As projects and environmental impacts grow larger, uncertainty looms larger than risk. The proper response to risk is to count it as a cost in expected value computations. However, the use of a single number (or expected value of risk) does not capture the risk variability or the range of values to be expected. Additionally, it does not allow for individual perceptions of risk. Precaution is one response to uncertainty – if the future cannot be perceived clearly, then the speed of advance should be tailored to the distance over which the clarity of vision is acceptable. In practice, the way risk and uncertainty are included in project appraisal work is through sensitivity analyses, which determine how the IRR is dependent on different variables. Using optimistic and pessimistic values for different variables can indicate which ones will significantly affect benefits and costs. Sensitivity analysis need not reflect the probability of occurrence of the upper or lower values. In project appraisal, deterministic point estimates of value could be quite misleading, whereas ranges of value help identify more robust options (Anderson and Quiggin, 1990). Various criteria, such as mini-max and minimum-regret may also be used (Friedman, 1986). The issue of uncertainty plays an important role in environmental valuation and policy formulation. Option values and quasi-option values are based on the existence of uncertainty (see Section 3.4.1). Option value (OV) is essentially the premium that consumers are willing to pay to avoid the risk of not having something available in the future. Among the definitions of OV, one useful measure is the difference between the ex-ante and ex-post welfare associated with the use of an environmental asset. The sign of OV depends upon the presence of supply or demand uncertainty, and on whether the consumer is risk-averse or risk-loving (Pearce and Turner, 1990). The quasi-option value (QOV) is the value of preserving options for future use in the expectation that knowledge will grow over time. If a project causes irreversible environmental damage, the opportunity to expand knowledge through scientific study of that asset is lost. Uncertainty about the benefits of preservation to be derived through future knowledge expansion (which is independent of development) yields a positive QOV. Thus development might be postponed until increased knowledge facilitates a more informed decision. If information growth itself depends on the development taking place, then the QOV is positive when the uncertainty concerns preservation benefits and negative when the uncertainty is about development benefits (Pearce and Turner, 1990). If calculations are performed in terms of the option price (valuing what a person would pay for future benefits today), then the OV may be redundant. The OV is added to expected future benefits to bring total value up to the option price. Most contingent valuation methods (CVMs) estimate the option price directly. Thus, the OV may be practically redundant if it is captured in other measures, although conceptually valid (Freeman, 1993).

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Environmental policy formulation is complicated by the presence of numerous forms of uncertainty. As an illustration, Bromley (1989) identified six different aspects of uncertainty in the case of air pollution resulting from acid deposition. They are (1) identification of the sources of particular pollutants; (2) ultimate destination of particular emissions; (3) actual physical impacts at the point of destination; (4) human valuation of the realized impacts at the point of destination; (5) the extent to which a particular policy response will have an impact on the abovementioned factors; and (6) the actual cost level and the incidence of those costs that are the result of policy choice. Policy makers address these uncertainties based on their perception of the existing entitlement structure. The interests of the future may be protected by an entitlement structure that imposes a duty on current generations to consider the rights of future generations – since unborn generations are unable to enter bids in today’s markets – to protect their interests. There are three policy instruments to ensure that future generations are not made worse off: mandated pollution abatement; full compensation for future damages (e.g. by taxation); and an annuity that will compensate the future for costs imposed in the present. In the face of uncertainty, the first option would appear to be the most practical. 3.7 Economy-wide policies and the environment Next, we turn to larger-scale issues that show how economy-wide policies (both macroeconomic and sectoral) may cause significant environmental and social harm. More details, including a historical review of ideas and recent case studies, are given in Chapters 7, 8 and 9. Fiscal and monetary policies, structural adjustment programmes and stabilization measures all affect the natural-resource base. Unfortunately, interactions among the economy, society and environment are complex, and our understanding of them is limited. Ideally, one would wish to trace the effects of economy-wide policy reforms (both macroeconomic and sectoral) through the socioeconomic and ecological systems. Time and data limitations generally preclude such comprehensive approaches in developing countries. Practical policy analysis is usually limited to a more partial approach, which traces the key impacts of specific economy-wide policies, at least qualitatively, and, wherever possible, quantitatively. No simple generalizations are possible as to the likely environmental and social effects of broad policy measures. Nevertheless, opportunities have been missed for combining poverty reduction- or efficiency-oriented reforms with the complementary goal of environmental protection – i.e. ‘win–win’ outcomes (Munasinghe, 1992a). For example, addressing problems of land tenure, as well as access to financial and social services, not only yields economic gains, but also are essential for promoting environmental stewardship. Similarly, improving the efficiency of industrial or energy-related activities would reduce both economic waste and environmental pollution (World Bank, 1992b–e). Many instances of excessive pollution or resource overexploitation are due to market distortions. Broad policy reforms, which usually promote efficiency or reduce poverty, could be made more beneficial for the environment. The challenge is to identify the complicated paths by which such policy changes ultimately influence conservation at the


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firm or household level. Some changes can have either beneficial or harmful environmental and social effects, depending on the nature of intervening conditions. The objective is not necessarily to modify directly the original broader policies (which have other conventional, non-environmental goals), but rather to design more specific complementary policy measures that would help mitigate negative effects or enhance the positive impacts of the original policies on the environment.

3.7.1 Macroeconomic policies During the economic crisis of the early 1980s, many developing countries that had been running substantial budget and trade deficits (and financing these by increasing external debt) were forced to adopt emergency stabilization programmes. These programmes often had unforeseen social and environmental consequences. One important environmental impact of the crisis was related to poverty and unemployment. The stabilization efforts often necessitated currency devaluations, controls on capital and interest rate increases. When income levels dropped, tax revenues decreased accordingly. As unemployment increased, governments fell back upon expansionary financing policies, which led to increases in consumer prices. The effect of such policies on the poorest population groups often drove them onto marginal lands, resulting in soil erosion or desertification. Fuel price increases and lowered incomes also contributed to deforestation and reductions in soil fertility, as the poor were forced to use fuelwood and animal dung for heating, lighting and cooking. Aside from the contractionary aspects of short-term stabilization measures, many macroeconomic policies also have potentially important effects on resource use and the environment. Unfortunately, no easy generalizations as to the directions of these effects are possible; they can be either beneficial or negative, depending on specific conditions. For example, real currency devaluations have the effect of increasing international competitiveness and raising production of internationally tradable goods (e.g. forestry and agricultural products). If the agricultural response occurs through crop substitution, environmental impact would depend on whether the crop being promoted tended to be environmentally benign (such as tea, cocoa, rubber) or environmentally damaging (such as tobacco, sugar cane, corn). Environmental impacts would also depend on whether increased production led to farming on new land (which could result in increased deforestation) or to more efficient use of existing farmland. Another possibility is that overvaluation of the exchange rate (and resulting negative terms of trade, decreased competitiveness of products and lower farmgate prices) may well push small cultivators onto more environmentally fragile marginal lands, in an attempt to absorb the effects of the price changes. The output from a natural-resource stock such as a forest or fishery will be affected by other factors, such as property rights (see Section 4.2). Thus, if trade policy increased the value of output (e.g. timber or fish exports), then the degree of ownership would influence how production and resource stocks were managed. Reactions might range from more investment in, and maintenance of, assets (if environmental costs were internalized by owner–users) to rapid depletion (when the users had no stake in the resource stock). Thus,

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Capistrano and Kiker (1990) propose that increasing the competitiveness of world exports would also increase the opportunity cost of keeping timber unharvested. This could lead to forest depletion that significantly exceeds natural regenerative capacity. Another study (Kahn and McDonald, 1995) used empirical evidence to suggest that a correlative link exists between debt and deforestation. They propose that debt burdens cause myopic behaviour that often results in overdepletion of forest resources – through deforestation rates that may not be optimal in the long run, but are necessary to meet short-term needs. Munasinghe and Cruz (1994) explicitly traced how economy-wide policy reforms to promote economic development could have numerous unanticipated environmental and social effects Table 3.1 summarizes some typical results. The first column lists only a few of the many economy-wide policy issues addressed through macroeconomic reforms. The policies in the second column are usually designed to address these issues, and the corresponding economic development objectives or direct impacts are given in the third column. The fourth column shows important second-order environmental and social impacts that may not be anticipated. While policy reforms could improve natural-resource management, some potential negative environmental impacts that concern us are given in this column. Thus, to evaluate such reforms properly, it would be necessary to assess their direct and indirect effects as well as the trade-offs between their conventional development contribution and their environmental effects. Relevant defensive measures or modifications may then be analysed for each policy. This systematic process is captured in the Action Impact Matrix (AIM) methodology (see Section 2.4.1). The key influence of macroeconomic policies on agriculture has already been shown by early studies (Johnson, 1973; Schuh, 1974). Krueger, Schiff and Valdes (1991) also show that economy-wide factors may be more important than sectoral policies in agriculture. When a broad assessment perspective is adopted, direct output price interventions by government have less effect on agricultural incentives than indirect, economy-wide factors, such as foreign exchange rates and industrial protection policies. The impact of economy-wide policies may also be important for the environment. For example, Hyde, Newman and Sedjo (1991) cite studies in Brazil and in the Philippines that demonstrate how economic policy spillovers constitute an important source of deforestation. Agricultural subsidies in Brazil probably contribute to half of the forest destruction in Amazonia (Binswanger, 1989; Mahar, 1988). A general equilibrium simulation for the Philippines suggests that foreign exchange rate changes, although motivated by general balance of payments concerns, have major implications for the demand for wood products, therefore influencing logging rates. The case of fuelwood may be as interesting, since fuelwood shortages have been identified as the major forestry problem in many developing countries. National price policies on fuel and investment policies on alternative energy sources may be important for addressing the fuelwood problem.

3.7.2 Structural adjustment Structural adjustment programmes address a well defined set of reform areas (see Section 7.2.1). These will generally include establishing an appropriate macroeconomic


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Table 3.1 Typical examples of direct and indirect environmental and social impacts of economy-wide policies Direct economic objectives/effects

Indirect (environmental and social effects)

flexible exchange rates

promote industrial competitiveness, exports; reduce imports

export promotion might promote more deforestation for export and lead to substitution of tree crops for annual crops; industrial job creation may reduce pressure on land resources

Food, security and unemployment

agricultural intensification in settled lands and resettlement programmes for new areas

increase crop yields and acreage; absorb more rural labour

may reduce spontaneous migration to ecologically fragile areas; however, there is potential for overuse of fertilizers and chemicals

Industrial protection, due to inefficient production

reduce tariffs and special investment incentives

promote competition and industrial efficiency

more openness may lead to more energy-efficient or less polluting technologies; it may also attract hazardous industries

Policy issue

Policy reform

Trade deficits

framework for growth, introducing a set of supporting sectoral policies and investment efforts and integrating the domestic economy into the world economy (Fischer and Thomas, 1990). Adjustment lending in the early l980s addressed problems of maintaining growth caused by the worldwide economic crisis. The crisis was triggered by the second round of energy price hikes, the collapse of export markets and increased international interest rates. These external conditions, combined with lack of competitiveness of local industries, lagging employment generation and persistent budget deficits, led to unsustainable current account deficits. Thus, trade-oriented reforms, including tariff reductions and devaluation, became key components of adjustment lending. Adjustment implications for managing external debt also received much attention. In turn, this led to concern for stimulating domestic savings, increasing the role of taxation in resource mobilization, decreasing the extent of government expenditures and making investments more productive. The benefits and costs of such programmes are country-specific. In a review of the Latin American experience, Birdsall and Wheeler (1992) conclude that there is no evidence to show that open developing country economies are more prone to pollution. The inflow of foreign technology and capital would tend to bring in better pollution standards. At the same

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time, it is the pollution-intensive heavy industries sector that has benefited from protective industrial and trade policies. Nevertheless, some concern persists that encouraging foreign investment and privatization might lead to the growth of ‘pollution havens’, given the weakness of environmental regulations in most developing countries. Trade liberalization also could encourage the growth of energy-intensive and/or highly polluting industry. However, pollution caused by industrialization could be offset by afforestation (although this does not necessarily compensate residents of polluted areas) and limited by appropriate taxation policies that encouraged the use of pollution-abatement technologies. The environmental relevance of structural adjustment reforms was reviewed by Cruz, Munasinghe and Warford (1997). The reforms included (l) relative price changes in agricultural outputs, inputs, energy and export taxes; (2) trade and industry policy reform; (3) changes in public expenditure programmes; and (4) institutional reforms by sector. In the early to mid l980s, environmental aspects were relatively neglected in adjustment lending operations, with few environmental loan components or conditionalities. The review also found that programmes from FY88–FY92 included more on the environment. For example, about 60% of the 58 countries reviewed had adjustment programmes whose loan components or conditionalities were environmentally related, compared with 37% during FY79–FY87. Sectoral adjustment programmes have also included environmental policy reforms. In the 1990s, international donor agencies, non-governmental organizations and academic institutions contributed to the debate on the environmental effects of structural adjustment and stabilization programmes. Several good studies exist of environmental and social impacts of country-wide policies (Abaza, 1995; Cruz et al., 1997; Environment and Development Economics, 1999; Kessler and Van Dorp, 1998; Munasinghe, 1992a; Munasinghe, 1996b; Munasinghe and Cruz, 1994; Opschoor and Jongma, 1996; Panayotou and Hupe, 1996; Reed, 1992, 1996; Warford, Munasinghe and Cruz, 1997; Young and Bishop, 1995) – see Chapter 7 for details.

3.7.3 Public investment/expenditure reviews Reductions in public expenditure are an integral part of many structural adjustment loans, and usually emerge from recommendations on spending priorities made in Public Investment/Expenditure Reviews (PI/ERs). The main purpose of PI/ERs is to provide recommendations to governments on the size and composition of their spending programmes and on ways to strengthen local institutions in ways that enhance country capabilities to design and implement such programmes. They have also been used to carry out basic sector work and to identify projects appropriate for World Bank support. PI/ERs facilitate expenditure decisions by the core planning and finance agencies, which are central to the key objectives of structural adjustment, poverty alleviation and sound management of natural resources. Public investment programmes often do not give adequate weight to environmental objectives as compared with efficiency and poverty alleviation. The potential exists for


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investment reviews to elevate environmental concerns appropriately and thereby help to avoid making investments that have some of the serious long-term environmental consequences. While the expenditure reviews are perhaps less crucial, these could be used to ensure, for example, that environmental agencies and their programmes receive a fair share of current government expenditures.

3.7.4 Sectoral policies While adjustment is inherently a macroeconomic effort, involving macroeconomic policy reform, it also requires specific sectoral reforms (Munasinghe and Cruz, 1994). The key macroeconomic variables in adjustment programmes are the investment–savings gap, the fiscal deficit, the trade deficit, the exchange rate and the rate of inflation. The microeconomic or sectoral reforms relevant to adjustment include industrial promotion and investment incentives, tax incidence, import liberalization and trade and energy pricing. These are undertaken to improve resource allocation, but they also have important implications for macroeconomic stability and growth (Fischer and Thomas, 1990). The first is primarily a microeconomic goal, while the second is an adjustment goal. For example, taxation and government expenditures are the prime microeconomic mechanisms for resource allocation. However, they also comprise the basic elements of fiscal policy. In turn, fiscal policy has a critical macroeconomic impact because it directly determines the fiscal deficit, and therefore affects the current account deficit and, after a lag, investment levels. Tax reform issues are particularly relevant from an environmental management perspective because they can have a wide range of potential impacts on resource use. The choice of the tax or tariff base can lead to substantial changes in the level of pollution-related activities. However, such environmental implications are not considered in conventional assessments that focus on fiscal effectiveness. Other sectoral reforms, such as those dealing with energy pricing and industrial exports, also affect macroeconomic stability, and have thus played a regular role in adjustment programmes (World Bank, 1989). Beyond their role in contributing to a stable macroeconomic environment, sectoral policies also have economy-wide relevance in terms of promoting growth from the supply side. These include sectoral investment and pricing policies, as well as sectoral regulation and institutional development. As noted by Fischer and Thomas (1990), the traditional approach to development was through investment in agriculture, industry, infrastructure and human resources. However, the contribution of these sectoral investments also depended largely on macroeconomic policies and the presence of enabling institutions. Some countries subsidize urban consumers by placing price ceilings on food. In such cases, the environmental consequences will be the same as for currency overvaluation, as both result in lowered incentives to increase production of internationally tradable crops. In the case of Brazil, Binswanger (1989) showed that general tax policies, special tax incentives, the rules of land allocation and the agricultural credit system all accelerate deforestation in the Amazon. These policies also increase landholding size and reduce the land available to the poor. Mahar (1989) traced many problems in the Amazon in Brazil to

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the decision in the mid 1960s to provide overland access to Amazonia. Further examples of sectoral work that address issues of environmental concern through economy-wide policy reform are given in Chapter 7, Munasinghe (1997) and Munasinghe and Cruz (1994).

3.7.5 National income accounts and macroeconomic performance In order to recognize accurately and include environmental concerns in macroeconomic analyses, standard national income accounting techniques must be re-examined. Performance is currently measured by the growth in gross domestic product (GDP), and policy reforms are justified routinely on the basis of their short-, medium- or long-term contribution to such growth. While GDP measures market activity reasonably well, it has been criticized for its neglect of other key aspects, such as non-market value added, income distribution and so on. Further, GDP does not consider depreciation of manmade capital (although the less quoted net domestic product, or NDP, does); it also leaves out the degradation of ‘natural capital’. Thus, GDP is an inaccurate measure of true, sustainable income. In terms of the environment, there are several shortcomings in the widely used traditional system of national accounts framework. (1) Natural and environmental resources are not fully included in balance sheets; therefore, national accounts represent limited indicators of national well-being, since they are a poor, or even ‘perverse’, measure of changes in environmental and natural-resource conditions. (2) Conventional national accounts fail to record the true costs of using natural resources in economic activity. The depletion or degradation of natural capital stocks (water, soil, air, minerals and wilderness areas), which occur due to productive activity, is not included in current costs or depreciation of natural wealth. Thus, resource-based goods are underpriced – the lower the value added, the larger is the extent of underpricing of the final product. Some countries promote primary product exports by subsidizing them, often with disproportionately large adverse impacts on the poor (who are less able to protect themselves) – the small cultivator, the forest dweller, the landless peasant and so on. If such hidden costs or ‘subsidies’ were estimated, the GDP of many countries could well be significantly lower. In addition, natural-resource depletion raises intergenerational equity issues, since productive assets available to future generations may be unfairly diminished (see Section 3.6.1). (3) Clean-up or abatement activities (e.g. expenditures incurred to restore environmental assets) often serve to inflate national income, while the offsetting environmental damages are not considered. For private firms, defensive environmental expenditures are netted out of final value added. In contrast, such clean-up costs are considered as productive contributions to national output if they are incurred by the public sector or households. GDP calculations are distorted in two ways, because undesirable outputs (like pollution) are overlooked, while beneficial environment-related activities are often implicitly valued at zero.

Such deficiencies in the accounting techniques employed up to the 1980s pointed to the need for a system of national accounts (SNA), which permits the computation of an environmentally adjusted net domestic product (EDP) and an environmentally adjusted net income (EDI). National-level decision makers and macroeconomic planners (typically in a ministry of finance or planning) routinely rely on the conventional SNA to formulate economic


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policies. Thus, a supplementary environmentally adjusted SNA and corresponding performance indicators would encourage policy makers to reassess the macroeconomic situation in light of environmental concerns and to trace the links between economy-wide policies and natural-resource management (Munasinghe and Cruz, 1994). Based on work carried out during the 1980s (Bartelmus, Stahmer and van Tongeren, 1989), the System for Environmentally adjusted Economic Accounts (SEEA) was created as an interim measure. Its objective was to integrate environmental data sets with existing national accounts information, while maintaining SNA concepts and principles insofar as possible. Environmental costs, benefits and natural-resource assets, as well as expenditures for environmental protection, were presented as satellite accounts in a manner consistent with the accounting framework of the SNA. The method involved disaggregation of the conventional SNA to highlight environmental relationships, linked physical and monetary accounting, imputations of environmental costs and extensions of the SNA production boundary – without modifying the core accounts. The SEEA framework received further impetus through the UN interim handbook on environmental accounting (UN, 1993), which outlined the possibilities for computing various national accounts aggregates such as ‘green GNP’ – that are adjusted downward to reflect the costs of net resource depletion and environmental pollution. Green net national product is a Hicks–Lindahl measure of potentially sustainable income (Hicks, 1946). However, it cannot indicate whether the saving rate can maintain this income indefinitely, and typically does not measure potential consumption if the economy were actually on a constant-utility path. ‘Genuine savings’ is a better measure of macrosustainability (Atkinson et al., 1997). Further work is outlined in Section 7.1.5. Following this, an operational handbook was published (UN, 2000b), and finally the Integrated Environmental and Economic Accounting Handbook was issued in 2003 (UN, 2003). The revisions provide methods to estimate environmental and natural-resourcerelated expenditures, which were not effectively captured in conventional SNA. Features include: (1) natural-resource asset accounts, which include natural-resource stock depletion and improve the balance sheets of the conventional SNA; (2) pollutant and material flow accounts, which report the use of energy and materials, and the generation of pollutants and wastes in the production process and the final demand: these accounts are linked to the supply and use tables of the IO table described in SNA; (3) environmental protection and resource management expenditures are shown more explicitly, and this data may be used for policy analysis and other research on sustainable development; and (4) better macroeconomic aggregates, such as environmentally adjusted net domestic product, have been developed. Natural-resource accounts have a balance sheet flavour, with their emphasis on opening and closing stocks in quantity and values of natural resources, including both commercial natural resources and non-commercial or environmental resources. Thus, resource accounts underlie the expanded national balance sheet accounts in the revised SNA. The principal policy and analytical uses of these accounts include: measuring physical scarcity, resource management, assessing the balance sheet of the resource sectors, productivity measurement,

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portfolio analysis and management, valuing depletion and identifying effects of environmental degradation. Natural-resource accounts, and their counterparts in the national balance sheet accounts, can therefore have wide use with regard to resource-management policies and broader environmental policies. Several countries have explored various environmental adjustments to the SNA (World Bank, 2006). Various measures of national product and wealth are under consideration, including natural resource (stock) accounts, resource and pollutant flow accounts, environmental expenditure accounts, and alternative national accounts aggregates (Atkinson et al., 1997). However, no countries have formally altered their SNA to reflect the environmental concerns in the 2003 revision to the SNA (UN, 2003), although pilot studies have been done. The simple measure introduced in Section 2.3.5 to indicate the sustainability of naturalresource stocks may be extended to cover total wealth per capita. The latter would be a useful indicator of sustainability, if the SNA aimed to measure total national wealth (including the value of stocks of manufactured capital, as well as living and non-living resources). For total wealth W and population P, development is (weakly) sustainable when S ¼ ½dðW=PÞ=dt=½W=P0: This index has several desirable properties – e.g. separately accounting for changes in natural assets having low substitution possibilities. Evolution of practical applications The World Bank, together with the UN Statistical Office (UNSO), completed early case studies in Mexico (van Tongeren et al., 1991) and Papua New Guinea (Bartelmus, Stahmer and van Tongeren, 1991) to determine how such accounts can be prepared. The Papua New Guinea study demonstrates the feasibility of applying the SEEA framework in a country with relatively weak institutional capacities and limited data availability (a scenario that would exist in many resource-rich developing countries). Depreciation of produced assets was calculated to be 9– 11% of GDP, resulting in a conventional NDP of between 89 and 91% of GDP. Environmental impacts were assessed for the agriculture, forestry, mining and energy sectors. The authors estimated that these impacts were about 2% of NDP on average, for the 1986–1990 time period. First, the environmentally adjusted net domestic product 1 (EDP1) was calculated, which incorporates the ‘economic’ depletion costs of natural-resource use (but does not account for the degradation of environmental quality and corresponding losses of non-marketed environmental services that is reflected in EDP2). Next, EDP2 was estimated after subtracting the costs of degradation of environmental quality from EDP1; EDP2 was estimated to range from 90 to 97% of NDP. The final results showed that consumption exceeded net environmentally adjusted domestic production in most years. However, lack of physical data made it extremely difficult to obtain accurate estimates. Significant fluctuations in commodity prices also reflect the difficulties for governments in attempting to maintain sustainable development policies. Additionally, contrary to findings, Papua New Guinea is not necessarily depleting its capital base, as the capital gain from erosion of external debt (caused by inflation reducing


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the value of the debt) is about 4% of GNP in real terms. The substitutability of capital is therefore an issue to be considered in the definition of ‘income’. In addition to these World Bank-supported studies, a few examples exist of the application of environmental accounting in developing countries (and even less in the developed world). The UN Economic Commission for Latin America and the Environment (ECLAC) and UNEP performed two case studies in Latin America that apply environmental accounting methodologies to limited areas within countries (CIDIE, 1992). The Argentina study valued a forest ecosystem by estimating the costs of improving productive functions and of maintaining ecosystem functions. Results gained were employed in modelling alternative management and exploitation scenarios. The Mexico study calculated adjustments to the gross product, due to a biological corridor, using market valuation of replacement cost in the agricultural and forestry sectors, and constructed physical balance sheets for individual resources. The Hicksian concept of income was utilized to provide a revised measure of the region’s income. Gilbert (CIDIE, 1992) did a study of Botswana using an environmental accounting framework within a larger modelling and information system. The approach used stock accounts (describing natural-resource stocks in physical units); resource user accounts (describing stocks in physical and monetary units); and socioeconomic accounts (focusing on resource use, demographics and environmental policy). However, full implementation of the framework has not been possible because of severe data constraints. An early application of environmental accounting in a developing country was performed by Repetto et al. (1989) for the World Resources Institute. The study collected data on petroleum, timber and soil resources. The approach used is based upon physical stock and flow accounts of natural resources and the valuation of these stocks. It has been suggested that the valuation method used in forestry overestimates the true resource depreciation, but has nevertheless proved extremely useful as an indicator of the magnitudes involved in adjustments to GDP through environmental accounting (CIDIE, 1992). A later study (WRI, 1991) utilized the same valuation methodology for forestry, but focused on providing detailed methods for the technical estimates of deforestation, soil erosion and coastal fishery overexploitation in Costa Rica. Recent work suggests that Bolivia may be on an unsustainable development path (World Bank, 2006). When depletion of natural resources is included, the genuine national savings rate became minus 3.8% of gross national income (GNI) in 2003, although the traditionally computed national savings rate was 12% of GNI. In this estimate, depletion of energy, metals and minerals was 9% of GNI and pollution damage was almost 7%, while the net forest depletion was zero. Some researchers have computed more composite indices of human welfare to show that the relationship between ‘true’ welfare and conventional income per capita is positive in the early development stage but becomes negative later – in contrast to the EKC effect (Daly and Cobb, 1989; Max-Neef, 1995). One such measure, called the index of sustainable economic welfare (ISEW), has already peaked in the 1970s or 1980s and is now declining for the USA, the UK, Germany, Austria and Netherlands. Poverty alleviation remains a dominant social

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objective (Sen, 1984). Lawn (2005) examines the valuation methods used to calculate the ISEW, the Genuine Progress Indicator and the Sustainable Net Benefit Index. He argues that a consistent and more robust set of valuation techniques is required in order for these alternative indexes to gain broad acceptability as a means of comparing the costs and benefits of growth. Recent work seeks to expand the social accounting matrix (SAM) to include the distributional impacts of environmental damage across income groups (Munasinghe, 2002a).

3.8 Appendix: Estimating and using shadow prices 3.8.1 Numeraire To derive a consistent set of economic shadow prices for goods and services, a common yardstick or numeraire to measure value is necessary. The same nominal unit of currency may have a different value depending on the economic circumstances in which it is used. For example, 1 rupee-worth of chocolate purchased in a duty free shop is likely to be more than the quantity of chocolate obtained for 1 rupee from a retail store (after import duties and taxes have been levied). Therefore, it is possible to distinguish intuitively between the border-priced rupee, which is used in international markets free of import tariffs, and a domestic-priced rupee, which is used in the domestic market subject to various distortions. The choice of the numeraire, like the choice of a currency unit, should not change the outcome of an economic decision – provided the same consistent framework and assumptions are used in the analysis. For example, only one difference exists between a cost–benefit study that uses ‘cents’ as units and another that uses ‘rupees’ (1 rupee is equal to 100 cents). In the analysis using cents, all quantities will be numerically 100 times larger than in the one using rupees. Since the analytical results will not be changed by this linear scale factor, one may choose the numeraire according to convenience. A most appropriate numeraire in many instances is a unit of uncommitted public income at border shadow prices (Little and Mirrlees, 1974). This unit is the same as freely disposable foreign exchange available to the government, but expressed in terms of units of local currency converted at the official exchange rate (OER). The border-priced numeraire is particularly relevant for the foreign exchange-scarce developing countries. It represents the set of opportunities available to a country to purchase goods and services on the international market.

3.8.2 Economic efficiency shadow prices The estimation and use of efficiency shadow prices is facilitated by dividing economic resources into tradable and non-tradable items. Tradables are directly imported or exported goods and services, and their values are already known in border prices – i.e. foreign exchange costs converted at the OER. Non-tradables are local goods whose values are known only in terms of domestic market prices, which must be converted to border prices by applying conversion factors (CFs). Hence,


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border ðshadowÞ price ¼ conversion factor domestic ðmarketÞ price; BP ¼ CF DP: For tradables with infinite elasticities (of world supply for imports and world demand for exports), the cost, insurance and freight (CIF) border price for imports and the free-on-board (FOB) border price for exports may be used (with a suitable adjustment for the marketing margin). If the relevant elasticities are finite, then the change in import or export costs, as well as any shifts in other domestic consumption or production levels or in income transfers, should be considered. The free trade assumption is not required to justify the use of border prices since domestic price distortions are adjusted by netting out all taxes, duties and subsidies. To clarify this point, consider a household where a child is given an allowance of 20 pesos a month as pocket money. The youngster may purchase a bag of sweets from a store at a price of 2 pesos. If the parents want to discourage consumption of sweets, they may impose a fine of 1 peso on each bag. The fine is exactly like an import duty, and the child must surrender 3 pesos for every bag of candy (valued at its domestic price, inside the household). From the family’s perspective, the total external payment for the item is only 2 pesos, because the 1 peso fine is a net transfer within the household. Therefore, the true economic cost (or shadow price) of the bag of lollipops to the household is 2 pesos (i.e. its border price), when the impact of the fine on the distribution of the income between parent and child is ignored. A non-tradable is conventionally defined as a commodity whose domestic supply price lies between the FOB export price and CIF import price. Items that are not traded at the margin because of prohibitive trade barriers, such as bans or rigid quotas, are also included within this category. If the increased demand for a given non-tradable good or service is met by the expansion of domestic supply or imports, the associated border-priced marginal social cost (MSC) of this increased supply is the relevant resource cost. If decreased consumption of other domestic or foreign users results, the border-priced marginal social benefit (MSB) of this foregone domestic consumption, or of reduced export earnings, would be a more appropriate measure of social costs. The socially optimal level of total consumption for the given input (Qopt) lies at the point where the curves of MSC and MSB intersect. Price and non-price distortions lead to nonoptimal levels of consumption, Q ≠ Qopt , where MSB ≠ MSC. More generally, if both effects are present, a weighted average of MSC and MSB should be used. The MSB is more important in a short-run, supply-constrained situation, while the MSC dominates in the longer run, when expansion of output is possible. The MSC of non-tradable goods and services from many sectors can be determined through appropriate decomposition. For example, suppose 1 peso-worth of the output of the construction sector (valued in domestic prices) may be broken down successively into components – such as capital, labour, materials, etc., which are valued at pesos C1, C2,…, Cn in border prices. Then the construction conversion factor (CCF, defined as the ratio of the border price to the domestic price) is given by

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CCF ¼

n X

Ci :

i¼1

The standard conversion factor (SCF) may be used with non-tradables that are not important enough to merit individual attention, or lack sufficient data. The SCF is equal to the OER divided by the more familiar shadow exchange rate (SER), appropriately defined. Using the SCF to convert domestic-priced values into border-price equivalents is conceptually the inverse of the traditional practice of multiplying foreign currency costs by the SER (instead of the OER) to convert foreign exchange to the domestic-price equivalent. The SCF is approximated by the ratio of the official exchange rate to the free trade exchange rate (FTER), when the country is moving toward a freer trade regime: SCF ¼

OER eX þ nM ; ¼ FTER eXð1 tx Þ þ nMð1 þ tm Þ

where X = FOB value of exports, M = CIF value of imports, e = elasticity of domestic supply of exports, n = elasticity of domestic demand for imports, tx = average tax rate on exports (negative for subsidy) and tm = average tax rate on imports. The foregone output of workers is the dominant component of the shadow wage rate (SWR). Consider unskilled labour in a labour surplus country, e.g. rural workers employed in an urban factory. Complications arise in estimating the opportunity cost of labour, because the original rural income earned may not reflect the marginal product of agricultural labour. Furthermore, for every new urban job created, more than one rural worker may give up former employment. Adjustments are also needed for seasonal activities, such as harvesting, and overhead costs, such as transport expenses. Then, the efficiency shadow wage rate (ESWR) is given by ESWR ¼ a m þ c u; where m and u are the foregone marginal output and overhead costs of labour in domestic prices, respectively, and a and c are corresponding conversion factors to convert these values into border prices. The appropriate shadow value placed on land depends on its location. Usually, the market price of urban land is a good indicator of its economic value in domestic prices, and the application of an appropriate conversion factor (such as the SCF) to this domestic price will yield the border-priced cost of urban land inputs. Rural land that can be used in agriculture may be valued at its opportunity costs – the net benefit of foregone agricultural output. The marginal social cost of other rural land depends on potential uses such as recreation (see Section 3.4). The shadow price of a capital is usually reflected in the discount rate or accounting rate of interest (ARI), which is defined as the rate of decline in the value of the numeraire over time (see Sections 3.2 and 3.6). In terms of pure efficiency, one practical proxy for the ARI is the opportunity cost of capital (OCC) – defined as the expected value of the annual stream of


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consumption, in border prices net of replacement, which is yielded by the investment of one unit of public income at the margin.

3.8.3 Adjustments for social (and environmental) shadow prices If social pricing is important, it is necessary to include the effect of changes on consumption patterns. Starting with the efficiency shadow wage rate (ESWR), suppose a worker receives a wage Wn in a new job and that the income forgone is Wo (both in domestic prices). We note that Wn may not necessarily be equal to the marginal product foregone m. It could be assumed, quite plausibly, that low-income workers consume the entire increase in income (Wn – Wo). Then this increase in consumption will result in a resource cost to the economy of b(Wn – Wo). The increased consumption also provides a benefit given by w(Wn – Wo), where w represents the MSB, in border prices, of increasing domestic-priced private sector consumption by one unit. Thus, we may estimate the following social shadow wage rate (adjusted for consumption effects): SSWR ¼ a m þ c u þ ðb wÞðW n W o Þ: Here b represents the MSC of increased consumption. If all new income is consumed, then b is the consumption conversion factor or resource cost (in units of the numeraire) of supplying consumers with one unit worth (in domestic prices) of the marginal basket of goods they would purchase: n X b¼ gi CFi ; i¼1

where, gi is the proportion or share of the ith good in the marginal consumption basket and CFi is the corresponding conversion factor. The corresponding MSB of increased consumption is given by: w = d/v. Here, 1/v is the value (in units of the numeraire) of a one-unit increase in domestic-priced consumption accruing to someone at the average level of consumption (ca). Therefore, v may be roughly thought of as the premium attached to public savings, compared to ‘average’ private consumption. Under certain simplifying assumptions, b = 1/v. Note that d is a form of ‘social weighting’ that favours the poor. If MU(c) denotes the marginal utility of consumption at some level c, then d = MU(c) / MU(ca). Assuming that the marginal utility of consumption is diminishing, d would be greater than unity for ‘poor’ consumers who are below the average level of income (i.e. c < ca), and vice versa. A simple form of marginal utility function could be as follows: MU(c) = c−n. Thus, d = MU(c) /MU(ca) = n(ca/c). Making the further assumption that the distribution parameter n = 1 yields d ¼ ca =c ¼ ia =i;

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where ia/i is the ratio of net incomes, which may be used as a proxy for the corresponding consumption ratio. In this simple case, the social weight d is equal to the income ratio. The consumption term (b – w) in the expression for SSWR disappears if, at the margin, (a) society is indifferent to the distribution of income (or consumption), so that everyone’s consumption has equivalent value (d = 1) and (b) private consumption is considered to be as socially valuable as uncommitted public savings (b = 1/v). A simple formula for the Social ARI or social shadow price of capital, which also includes consumption effects, is given by SARI ¼ OCC½s þ ð1 sÞw=b; where s is the fraction of the yield from the original investment that will be saved and reinvested. Adjustments for environmental shadow prices are based on environmental externalities (see Section 3.4). Since the rigorous estimation of shadow prices is a long and complex task, it is advisable to use whatever shadow prices have already been calculated. Alternatively, one might estimate a few important items, such as the standard conversion factor, opportunity cost of capital and shadow wage rate. When the data are not precise enough, sensitivity studies may be made over a range of values of such key national parameters.

4 Ecological and social aspects1

This chapter provides an in-depth discussion of the linkages between the environmental and socioeconomic domains of sustainable development, institutional settings and environmental and social assessments. Some ideas underlying the sustainability of ecological and social systems were discussed earlier in Chapter 2. The basic role of ecosystems in supporting human society and economic activities, and methods of assessing this contribution (including monetary valuation), were explained in Chapter 3. These ideas are extended in Section 4.1, which summarizes the comprehensive conceptual framework based on the Millennium Ecosystem Assessment (MA), including the cyclic interactions between ecological and socioeconomic systems, and the main ecosystem services which sustain human well-being. The MA highlights the precarious situation of many critical ecosystems. The idea of ‘panarchy’ of living systems, and dynamic ecological cycles involving birth, growth, adaptation, decay, death and regeneration, help us understand ecosystem behaviour. Section 4.2 describes the key mediating role played by property rights regimes in determining how societies exploit natural resources. Property rights regimes play an important role in designing and implementing sustainable environmental management measures. Their effectiveness largely depends on the congruency of well specified property rights regimes with ecological and social factors, especially in the case of traditional societies and native peoples who are heavily dependent on ecological resources, as well as the landless poor who subsist in degraded areas. Finally, in Section 4.3, environmental and social assessments are described as important elements of sustainable development assessment, which complement cost–benefit analysis (or economic assessment).

4.1 Conceptual framework linking ecological and socioeconomic systems The Millennium Ecosystem Assessment (MA) was launched by United Nations SecretaryGeneral Kofi Annan in 2000 (UN, 2000a). Conducted during 2001–2005, the goal of the MA was to assess the impacts of ecosystem change on human well-being and then identify 1

The valuable contributions of S. Hanna, W. Reid and W. Shearer to this chapter are gratefully acknowledged. Some parts of the chapter are based on material adapted from Hanna and Munasinghe (1995c), Munasinghe (1992c), Munasinghe and Reid (2005) and Munasinghe and Shearer (1995).

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the actions needed to enhance the conservation and sustainable use of those systems and their contribution to human well-being. Briefly, an ecosystem is a ‘dynamic complex of plant, animal and micro-organism communities and their non-living environment interacting as a functional unit’ (CBD, 1992). The MA results provide valuable inputs to the work of four international environmental treaties – the UN Convention on Biological Diversity, the Ramsar Convention on Wetlands, the UN Convention to Combat Desertification and the Convention on Migratory Species. The work was supported by 22 of the world’s leading scientific bodies and involved more than 1360 experts from 95 countries. Their findings on the condition and trends of ecosystems, scenarios for the future, possible responses and assessments at a sub-global level are set out in technical reports (MA, 2005c, d, e, f). Several synthesis reports draw on these detailed studies to answer questions posed by specific groups of users.

4.1.1 Ecosystem services and human well-being Figure 4.1 summarizes the complex, circular and dynamic relationship between the ecological and socioeconomic (development) domains. The large horizontal arrows at the top and bottom indicate the cyclic relationship. Starting from the top, ecosystem services have social, economic and environmental impacts, from which alternative future development paths will emerge, with different consequences for human well-being. The alternative development scenarios affect indirect drivers of change, which in turn influence direct drivers of change (two downward arrows). The two upward vertical arrows also indicate key feedback effects between both indirect and direct drivers and human well-being. Finally, the direct drivers have important impacts on ecosystems and their services.

Ecological domain

soc., econ., env.

Ecosystem services

Development domain

Alternative development scenarios (human well-being)

– provisioning – regulating

indirect drivers

– cultural – supporting direct drivers

Figure 4.1. Circular interaction between ecological and development (socioeconomic) domains.

4 Ecological and social aspects

113 Constituents of well-being

Ecosystem services

Security personal safety secure resource access security from disasters

Provisioning food fresh water wood and fibre fuel etc.

Supporting nutrient cycling soil formation primary production etc.

Basic material for good life

Regulating climate regulation flood regulation disease regulation water purification etc.

Cultural aesthetic spiritual educational recreational etc.

adequate livelihoods sufficient nutritious food shelter access to goods

Health strength feeling well access to clean air and water

Freedom of choice and action opportunity to be able to achieve what an individual values doing and being

Good social relations social cohesion mutual respect ability to help others

Life on Earth – biodiversity potential for mediation by socioeconomic factors

intensity of linkages between ecosystem services and human well-being

low

weak

medium

medium

high

strong

Figure 4.2. How ecosystem services sustain key components of human well-being.

Indirect drivers include the following major components: demographic; economic (globalization, trade, market and policy framework); sociopolitical (governance and institutional framework); science and technology; cultural and religious. Direct drivers include the following main elements: changes in land use; species introduction or removal; technology adaptation and use; external inputs (e.g. irrigation); resource consumption; climate change; bio-geophysical drivers (e.g. volcanoes). Figure 4.2 further elaborates the basic linkages in Figure 4.1, by providing an overview of the key ways in which ecosystems and their services support and affect human well-being (see also Chapter 3 and MA (2005c)). Overall supporting services The left-hand side of Figure 4.2 shows that all other ecosystem functions (provisioning, regulation and cultural) ultimately depend on a set of broad supporting services, which include soil formation, nutrient cycling, primary production, etc. Provisioning services Ecosystems provide products to support human activities and consumption, including food, fresh water, fuelwood, fibre, biochemicals and genetic resources.

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Regulating services Ecosystems regulate natural processes and purify natural resources, affecting areas such as climate, disease and water. Cultural services Ecosystems yield non-material benefits, including spiritual and religious support, recreation and ecotourism, aesthetic pleasure, inspiration, education, sense of place and cultural heritage. We note that provisioning, regulating and cultural ecosystem services correspond roughly to the respective categories of economic value – direct-use value, indirect-use value and nonuse value, defined in Chapter 3. The right-hand side of Figure 4.2 summarizes the elements of human well-being which are supported by ecosystem services, with the width and shading of each arrow indicating the intensity of the linkage and the potential for human mediation, respectively. The expansion of freedoms and options intrinsic to the sustainable development process (Chapter 2) is associated with the following constituents of human well-being: security; basic material needs; health; good social relations. In Section 4.2, this underlying conceptual framework is used to study how property rights regimes embedded in the fabric of human communities influence the way in which environmental resources are used.

4.1.2 Main findings of the Millennium Ecosystem Assessment Based on the foregoing framework, the MA arrived at a number of key conclusions (MA, 2005a, 2005b). Major issues All human beings depend on nature and ecosystem services for their well-being (Figure 4.3). We have made unprecedented changes to ecosystems in recent decades to meet growing demands for food, fresh water, fibre and energy, and to improve the lives of billions. These changes have weakened nature’s ability to deliver other key services, such as purification of air and water, protection from disasters and the provision of medicines. About 60% of the ecosystem services that support life on Earth (e.g. fresh water, capture fisheries, air and water regulation and the regulation of regional climate, natural hazards and pests), are being degraded or used unsustainably. Specific problems include: the dire state of many of the world’s fish stocks; great vulnerability of two billion people living in dry regions to the loss of ecosystem services (especially lack of water resources); growing pressure on ecosystems from climate change and nutrient pollution. The loss of services derived from ecosystems is a significant barrier to the achievement of the Millennium Development Goals (MDGs), especially the reduction of poverty, hunger and disease.

4 Ecological and social aspects Mountain and polar food fibre fresh water erosion control climate regulation recreation and ecotourism aesthetic values spiritual values

Inland water (rivers and other wetlands)

Forest and woodlands

fresh water food pollution control flood regulation sediment retention and transport disease regulation nutrient cycling recreation and ecotourism aesthetic values

food timber fresh water fuelwood flood regulation disease regulation carbon sequestration local climate regulation medicines recreation aesthetic values spiritual values

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Cultivated

Coastal

food fibre fresh water dyes timber pest regulation biofuels medicines nutrient cycling aesthetic value cultural heritage

food fibre timber fuel climate regulation waste processing nutrient cycling storm and wave protection recreation and ecotourism aesthetic value

Drylands food fibre fuelwood local climate regulation cultural heritage recreation and ecotourism spiritual values

Urban (parks and gardens)

Marine

air quality regulation water regulation local climate regulation cultural heritage recreation education

food climate regulation nutrient cycling recreation

Island food fresh water recreation and ecotourism

Figure 4.3. Ecosystems and some of the services they provide.

A further threat to our well-being has arisen from human activities that have taken the planet to the edge of a massive new wave of species extinctions. Fossil records indicate that the historical extinction rate was less than one species per 1000 every 1000 years. In recent years, this extinction rate has increased between 100- and 1000-fold. Projected future extinction rates are likely to be ten times higher. The degradation of ecosystems will increase globally in coming decades, unless human attitudes and actions change. The current status and continuing decline of 15 of the 24 ecosystem services examined in the MA has increased the likelihood of abrupt changes that will seriously affect human well-being. Such changes include the emergence of new diseases, sudden loss of water quality, creation of ‘dead zones’ along the coasts, the collapse of fisheries and shifts in regional climate. Only provisioning services such as crops, livestock and aquaculture show gains. Policy options and remedies Some important steps to protect and manage ecosystem services more sustainably are summarized in Box 4.1. Measures to conserve natural resources will be more successful if local communities are empowered by giving them ownership of these resources, a fair share of the benefits and a greater role in decision making. Even the technology and knowledge available today could considerably reduce human impacts on ecosystems. However, such measures are unlikely to be deployed fully until the full value of ecosystem services is taken into account.

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Box 4.1 Measures taken to manage ecosystem services more sustainably Change the economic background to decision making *

*

*

*

Ensure the value of all ecosystem services, not just those bought and sold in the market, are taken into account when making decisions. Remove subsidies to agriculture, fisheries and energy that cause harm to people and the environment. Introduce payments to landowners in return for managing their lands in ways that protect ecosystem services, such as water quality and carbon storage, which are of value to society. Establish market mechanisms to reduce nutrient releases and carbon emissions cost-effectively.

Improve policy, planning and management *

*

*

*

*

Integrate decision making between different departments and sectors, as well as international institutions, to ensure that policies are focused on protection of ecosystems. Include sound management of ecosystem services in all regional planning decisions and in the poverty-reduction strategies being prepared by many developing countries. Empower marginalized groups to influence decisions affecting ecosystem services, and recognize in law the local communities’ ownership over natural resources. Establish additional protected areas, particularly in marine systems, and provide greater financial and management support to those that already exist. Use all relevant forms of knowledge and information about ecosystems in decision making, including the knowledge of local and indigenous groups.

Influence individual behaviour * *

*

Provide public education on why and how to reduce consumption of threatened ecosystem services. Establish reliable certification systems to give people the choice to buy sustainably harvested products. Give people access to information about ecosystems and decisions affecting their services.

Develop and use environment-friendly technology *

* *

Invest in agricultural science and technology aimed at increasing food production with minimal harmful trade-offs. Restore degraded ecosystems. Promote technologies to increase energy efficiency and reduce greenhouse gas emissions. Source: Taken from MA (2005f).

Better protection of natural assets will require coordinated efforts across governments, businesses, civil society and international institutions. The state of ecosystems will depend, inter alia, on critical policy choices concerning investment, trade, subsidies, taxation and regulation.


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4.1.3 Dynamics of interlinked living systems Chapters 2 and 3 indicated that socioeconomic and ecological systems are closely linked and have co-evolved dynamically within a larger complex adaptive system over a long span of time. In this section, we briefly summarize the dynamics of such a ‘panarchy’ of systems, using the cycle of growth, adaptation, transformation, collapse and regeneration described by Gunderson and Holling (2001). Box 2.2 introduced panarchy as a nested hierarchy of living systems and their adaptive cycles across scales. Figure 4.4 shows how a system at a given level is able to operate in its stable (sustainable) mode, because it is protected by the slower and more conservative changes in the super-system to which it belongs. At the same time, the system will be invigorated and energized by the faster cycles taking place in the many sub-systems within it. In brief, both conservation and continuity from above, and innovation and change from below, are integral to the panarchy-based approach, helping to maintain the dynamic balance between the twin requirements for stability and for change. The dynamic path of a given system (ranging in scale from a cell to a biome) is shown in Figure 4.5. The cycle shows four phases: (1) entrepreneurial exploitation (r); (2) conservation and organizational consolidation (K); (3) release and creative destruction (Ω); and (4) reorganization and destructuring (α). Each phase is characterized by different degrees of potential (ability to develop and grow) and connectedness (internal linkages and structure). Using the example of the centuries-long evolution of a forest, the first part of the cycle shows exploitation of novelty to grow and evolve from pioneer species (r) to climax species (K). Accumulation of biomass and wealth results in reduced resilience and increased vulnerability, raising the risk of destruction due to major disturbances such as fire, storm or pest (Ω). This is followed by the release of accumulated nutrients and biomass, which may be reorganized into the start of a new cycle (α). Each phase of the cycle creates the conditions for the next phase.

bigger and longer lived

super-system (slower changes) conservation and continuity from above

(sustainable) system

innovation and adaptation from below (faster changes) sub-systems

Figure 4.4. Dynamic interaction and continuity of living systems across scales.

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α

K

conservation

potential

rganization reo

x

n tio exploita

as rele

e

Ω

r connectedness

Figure 4.5. Cycle of growth and reorganisation for living systems.

The slower and steadier ‘forward loop’ consists of the first two ‘growth’ phases, while the less predictable ‘backward loop’ includes the second two ‘reorganization’ phases. Resilience is a key concept, which indicates the ability of a system to continue functioning within normal limits when externally perturbed and maintain the component elements needed to renew or reorganize if a large shock significantly changes system structure and function (Walker et al., 2002). The more resilient the system, the more sustainable it is. If a third axis of resilience is included in the analysis, the figure-eight shape in Figure 4.5 becomes the twisted but non-intersecting loop shown in Figure 4.6. Each system is still a part of the panarchy shown earlier in Figure 4.4. Thus the exploitation phase (r) of a smaller system could trigger change or revolt in the larger system to which it belongs, while the consolidation phase (K) of a larger system will stabilize and facilitate reorganization of a subordinate system. Holling (2004) argues that the concept of panarchy could be extended also to study how social systems grow, adapt, transform and collapse. The backward loop (usually involving abrupt change) is a critical time when opportunities arise for experimentation and learning – systems face risk and their resilience is tested and established. As we consider the long-term co-evolution of socioeconomic and ecological systems, it would be useful to determine if we are entering into a phase of higher risk, during such a backward loop, by assessing the changes brought about by the challenges described in Chapter 1.

4.2 Property rights, governance and ecological–social linkages Next, we examine the institutional dimensions of environmental–social sustainability. Humans interact with their environment through systems of property rights and governance


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K

potential

α

r Ω

con

nec

ted

nes

s

ce

lien

resi

Figure 4.6. Adding the third dimension of resilience unravels the twist in the two-dimensional figureeight shape of Figure 4.5.

(that are embedded in social, political, cultural and economic context), and thereby affect both the quantity and quality of environmental resources. While national and international economic policies have often ignored the environment, institutions could play a key role in reconciling economic development and the maintainance of environmental-carrying capacity and resilience (Arrow et al., 1995a; Grima et al., 2003). Ecology and Society (2006) and Environment and Development Economics (2006) describe recent research on resilience in social–ecological systems. Folke and Gunderson (2006) identify several papers that explain how better ecological–social research can help to address global environmental issues. We explain in the following how the functioning of property rights regimes, in relation to human use of the environment, is critical to the design and implementation of sustainable environmental management measures (Hanna and Munasinghe, 1995c).

4.2.1 Sustainability, sustainable development and property rights regimes Property rights regimes consist of property rights, bundles of entitlements defining rights and duties in the use of natural resources, and property rules, the rules under which those rights and duties are exercised (Bromley, 1991). Property rights regimes influence the use of environmental resources, a fact that has long been well established, if not well practiced. Anderson (1983) wrote of the dangers of fisheries overexploitation without ownership, an argument already noted by Gordon (1954). In ‘The tragedy of the commons’, Garrett Hardin (1968) focused widespread attention on the problem of environmental degradation in the

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absence of rules governing use. For many years, the general interpretation of Hardin’s argument was that collectively owned property was the culprit, and that private property was necessary to sustain environmental resources. However, a rapidly expanding body of scientific evidence indicates that sustaining environmental resources is not dependent on a particular structure or type of property regime, but rather on a well specified property rights regime and a congruency of that regime with ecological and social factors. In this ecological and social context, sustainability is a difficult concept to interpret because it has a wide range of meanings based on different disciplines and world views. What is being sustained, how it is to be sustained, and for how long, are all open to interpretation. Regardless of the specific meaning used, it is clear that, to some extent, sustainability is a human construct. Humans use their environment for a range of objectives (see Section 4.1.1), which leads to different expectations as to what is to be sustained and who is to have claims on environmental services. Cochrane (2006) argues that social (cultural) capital determines the sustainability of environmental capital by influencing management objectives, efficiency of use and demand relating to natural-resource use (see Chapter 2). The question of sustainability is a complicated one, the answer to which involves more than the generic application of a property rights regime. Property rights regimes need to reflect both general principles and specific social and ecological contexts, in order to be effective in modulating the interaction between humans and their environment. General principles include the structural and functional attributes of property rights regimes that transcend a particular context (Hanna, Folke and Maler, 1996). General principles are the necessary conditions for effective property rights regimes, because a property rights regime cannot succeed over the long run without them. They include several key elements, such as congruence of ecosystem and governance boundaries; specification and representation of interests; matching of governance structure to ecosystem characteristics; containment of transaction costs; monitoring, enforcement and adaptation processes at the appropriate scale (Bromley, 1991; Eggertsson, 1990; Hanna, 1992; Ostrom, 1990). General principles are necessary, but not sufficient in themselves, for effective property rights regimes. In addition, specific attributes of social and ecological context must be represented. Social contexts contain all the dimensions of the human relationship to environmental resources, including social arrangements, cultural practices, economic uses and political constraints. Ecological contexts contain the structure of ecosystems in which humans live and work, as well as the particular functional properties of those ecosystems. The particular details of the social and ecological context are what give a human social– environmental interaction its variety and detail. The match between a property rights regime and the contextual characteristics of the affected humans and ecosystems will determine success or failure in terms of sustainability. Better economic valuation of environmental and sociocultural assets (see Chapter 3), and their internalization in the price system, is one means of ensuring that market forces lead to more sustainable resource use. The more equitable distribution of resources and assets is a step toward poverty reduction and social sustainability, as is greater participation and


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empowerment of disadvantaged groups. Clearly, property rights regimes that specify access to the natural-resource base and rights of use have a crucial role to play in this context. The literature addressing questions of property rights and natural-resource use is growing, but there are large gaps in knowledge (Hanna and Munasinghe, 1995c). Five of these areas are explored below.

4.2.2 Governance systems Questions of governance over environmental resources have to do with the ability to predict and oversee probabilistic ecosystem responses to human behaviour and management, and to external drivers such as climate. Complexity of the human systems and ecosystems affects the ability to extract consistent objectives, design meaningful control systems and monitor response. The scale of the ecosystem in comparison with scales of social organization or legal jurisdiction determines the extent of the match between the human and environmental systems. The delineation and coordination of authority over environmental decisions is critical to relating actions to outcomes. The way in which governance is coordinated between authorities at different levels determines consistency across scales. The success of decentralized governance systems may be improved by applying the principle of subsidiarity, which requires that each decision is made and implemented at the lowest practical and effective level. Most studies assume that the manager is outside the system being managed (Walker et al., 2002). However, in the context of long-term sustainability, linked socioeconomic and ecological systems (SESs) behave as complex adaptive systems, with the managers as integral components of the system. Ostrom (1995) argues that, since many biological processes occur at small, medium and large scales, governance arrangements that can cope with this level of complexity also need to be organized at multiple scales and linked together effectively. The importance of nested institutional arrangements is emphasized, with quasi-autonomous units operating at very small, up to very large, scales. The concept of distributed governance is analysed by Townsend and Pooley (1995a) using competing models of cooperative management, co-management and rights-based management in the context of fisheries. They pay attention to both internal and external governance issues. Fitzpatrick (2000) also looks at distributed governance in Canada. He emphasizes that there is a need for partnership arrangements, especially between multiple sectors and levels of governance to meet shared objectives. Distributed authority affects governance efficiency, in particular through the role played by user participation in lowering management costs (Hanna, 1995). The contribution of user participation to governance efficiency may be analysed in terms of the structure and function of user participation and its effect on management costs. Kaitala and Munro (1995) address the question of governance coordination over multiple jurisdictions, as exemplified by transboundary fishery resources categorized as highly migratory fish stocks and straddling fish stocks. The high-seas portion of the stocks are exploited by both coastal states and distant-water fishing nations. The difficult issue of managing such resources (characterized by ill defined property rights over

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the high-seas portion of the resources) is the focus of a major United Nations intergovernmental conference. Several case studies illustrate the application of the various principles of governance to the environmental challenges of air pollution, fishery management and pesticide use. Tietenberg (1995) examines the question of governance design and scale through an analysis of the use of market-based mechanisms on the transferable permits approach to pollution control problems in the United States. From the various examples described, he extracts lessons for both the implementation process and programme design. Townsend and Pooley (1995b) consider the question of appropriate levels of authority – through a potential application of the distributed governance concept to the lobster fishery of the northwestern Hawaiian Islands. Gren and Brännlund (1995) show that, although geographic differences in environmental impacts may call for region-specific environmental regulations, regional differences in enforcement costs will lead to different levels of cost-effective regulation. Grima, Horma and Kant (2003) discuss the role of institutions at the international, national and community levels (including property rights) in making the forestry sector development more sustainable.

4.2.3 Equity, stewardship and environmental resilience Generally, the degree of equity represented by a property rights regime helps to create the incentive structure which either promotes or inhibits stewardship of environmental resources. In turn, the degree of stewardship practiced affects the level of ecosystem resilience. Exactly how equity affects stewardship, and how specific stewardship practices affect resilience, are still matters of research. Definitions of equity, stewardship practices and environmental resilience reflect a combination of local context, appropriate incentive structures and adaptation to environmental change. The goals of equity and stewardship are commonly considered to be inconsistent with efficiency in environmental management. In a departure from the usual approach, Young and McCay (1995) look at efficiency-driven, market-based property rights systems and evaluate them for their ability to accommodate equity, stewardship and resilience in the design of adaptive and flexible management regimes – after considering a number of different types of property rights systems for a variety of resources. Chichilnisky and Heal (2000) emphasize that the most attractive feature of markets is efficient allocation of resources, requiring minimal intervention once an appropriate legal infrastructure is in place. Several studies demonstrate the difficulties of crafting equitable schemes that promote better stewardship and resilience for the conservation of natural resources. Gadgil and Rao (1995) examine the incentives for managing biodiversity contained in India’s folk traditions of nature conservation. They focus on the efficiency and equity gains possible through reestablishing conservation approaches based on positive incentives to local communities. This attractive option is contrasted with current unsuccessful regulatory methods that are too centralized, sectoral and bureaucratic. Zylicz (1995) analyses the conflict between conservationists and a municipality in northeastern Poland, in which (i) areas of national parks are


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being claimed by previous landowners who feel they were not reimbursed fairly, (ii) there are private or communal enclaves left within park boundaries and (iii) neighbouring landowners protest against development constraints due to the park’s existence. The fate of nature depends on the ability of conservationists to demonstrate economic benefits from investing in natural capital to prevent degradation. Parks and Bonifaz (1995) examine the joint use of environmental resources by looking at the inconsistencies of short-term commodity production with long-term environmental sustainability in open-access Ecuadorian mangrove–shrimp systems. They identify incentives to maximize short-term profits through shrimp mariculture, which have led to destruction of larval-shrimp habitats as mangrove ecosystems were converted to shrimp ponds. Gottret and White (2001) describe integrated natural-resource management (INRM) in Latin America. The complexity of INRM interventions requires a more holistic approach to impact assessment, which combines the traditional ‘what’ and ‘where’ factors of economic and environmental priorities, with newer ‘who’ and ‘how’ aspects of social actors and institutions.

4.2.4 Traditional knowledge The documentation and use of traditional ecological knowledge is now an internationally accepted practice. At an even deeper level, many ‘modern’ concepts such as ‘Gaia’ and ‘deep ecology’ have basic roots in ancient philosophies – e.g. the contribution of eastern thinking is documented in Daniels (2005), Hall (1989) and Hargrove (1989). Here we focus on how long-standing systems of environmental-resource management and their use of traditional ecological knowledge are yielding insights into current resourcemanagement problems. Cicin-Sain and Knecht (1995) review data on reconciling systems of traditional knowledge with modern approaches to the management of natural resources. They analyse implementation challenges that both regional- and national-level entities will face as they endeavour to enhance the role of indigenous knowledge and participation. Ecosystems are complex adaptive systems, and their governance requires flexibility and a capacity to respond to environmental feedback (Berkes, Colding and Folke, 2000; Dietz, Ostrom and Sten, 2003; Levin, 1998). Carpenter and Gunderson (2001) stress the need for continuously testing, learning about and developing knowledge and understanding in order to cope with change and uncertainty in complex adaptive systems. Knowledge acquisition about complex systems seems to require institutional frameworks and social networks nested across scales to be effective (Berkes, Colding and Folke, 2003). Knowledge of resource and ecosystem dynamics and associated management practices exists among people of communities that, over long periods of time, interact for their benefit and livelihood with ecosystems (Berkes et al., 2000; Fabricius and Koch, 2004). The way such knowledge is being organized and culturally embedded, its relationship to institutionalized, professional science and its role in catalysing new ways of managing environmental resources have all become important subjects (Armitage, 2003; Brown, 2003; Davis and Wagner, 2003; Gadgil et al., 2000; Kellert et al., 2000). It has been suggested that the

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management and governance of complex adaptive systems may benefit from the combination of different knowledge systems (Johannes, 1998; Ludwig, Mangel and Haddad 2001; McLain and Lee, 1996). Some attempt to import such knowledge into the realm of scientific knowledge (Mackinson and Nottestad, 1998), while others argue that these knowledge systems are culturally evolved and exist as knowledge–practice–beliefs complexes that are not easily separated from their institutional and cultural contexts (Berkes, 1999). There are those who question the role of traditional and local knowledge systems in the current situation of pervasive environmental change and globalized societies (Du Toit, Walker and Campbell 2004; Krupnik and Jolly, 2002), while others argue that there are lessons from such systems for complex systems management, which also need to account for interactions across temporal and spatial scales as well as organizational and institutional levels (Barrett et al., 2001; Pretty and Ward, 2001), and in particular during periods of rapid change, uncertainty and system reorganization (Berkes and Folke, 2002). The use of traditional and non-technical knowledge by itself, in combination with modern scientific knowledge and in the restoration of previously established property rights, is explored in several case studies. Pálsson (1995) considers the use of practical knowledge obtained by Icelandic fishing skippers in the course of their work, exploring how fishermen’s knowledge differs from that of fishery scientists, and how the former could be brought more systematically into the process of resource management for the purpose of ensuring resilience and sustainability. A study of Cree Indians from the Canadian subarctic is presented by Berkes (1995), who analyses the evidence regarding the distinctions of the local indigenous knowledge from Euro-Canadian, science-based wildlife and fishery management knowledge. The understanding of traditional knowledge for resource management has remained elusive, not only for development policy makers, but also for scholars engaged in such research. Traditional knowledge may be used to re-establish claims to former rights (Ruddle, 1995). For the New Zealand Maori, traditional property rights have been recognized by customary law. The codification of existing rights and customary laws within a system of statutory law in various cultural settings is a contemporary process in many nations in the Pacific Basin, which might provide useful precedents for application worldwide. Long, Tecle and Burnette (2003) reveal that myths, metaphors, social norms and knowledge-transfer between generations of the White Mountain Apache tribe facilitate collective action and understanding of ecosystem dynamics, and provide a cultural foundation for adaptive management and modern ecological restoration. Watson, Alessa and Glaspell (2003) argue that traditional ecological knowledge serves an important function in the long-term relationships between indigenous people and vast ecosystems in the circumpolar north, and that it can contribute to understanding the effects of management decisions and human-use impacts on long-term ecological composition, structure and function. Ghimire, McKey and Thomas (2004) assess variation in knowledge relating to the diversity of medicinal plant species, their distribution, medicinal uses, biological traits, ecology and management within and between two culturally different social groups living in villages in northwestern Nepal. Devkota (2005) describes how traditional knowledge


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embedded in Nepalese forest communities enhances natural, social and economic systems simultaneously, and provides a practical example of strong sustainability. These local groups are not only meeting their present demand for natural-resource services, but also seeking to increase their socioeconomic and environmental resources for the future. Becker and Ghimire (2003) show the important role of organizations such as NGOs, in bridging traditional knowledge and scientific insights, and in providing social space for mobilizing a synergy between traditional knowledge and western knowledge for sustaining ecosystem services and biodiversity in Ecuadorian forest commons. Milestad and Hadatsch (2003) analyse the potential for organic farming in the Austrian Alps to flourish under the Common Agricultural Policy of the European Union in relation to the farmers’ perspectives on sustainable agriculture, and whether or not organic farming and traditional practices are capable of building social–ecological resilience in the area.

4.2.5 Mechanisms linking humans and environmental resources Linkages between humans and environmental systems operate in different ways according to their structure, the systems they link and the process by which the linkage is made. Some linkages are constructed by the informal observation of environmental characteristics on the part of users and the gradual evolution of behavioural response. Others are established as more rapid responses to change. In cases of environmental overuse, linking mechanisms are often weak or absent, cutting off the interaction between environmental condition and human response. The particular structure of a linking mechanism reflects the economic, social and ecological context in which it is established. The structure determines what information will be monitored, how it will be monitored and what will be done with the information once it is acquired. The key question is whether the governance system promotes, or even allows, behavioural adaptation to environmental change. Linkages affect both ecosystem and human system adaptation and evolution through the type of feedback allowed. Folke and Berkes (1995) present a systems view of social and ecological interactions, which stresses the need for active social adaptation to environmental feedback and the use of traditional ecological knowledge. Particular attention is paid to the lessons that can be learned to assist in the design of more sustainable resource management systems – improving their adaptiveness and resilience. Chopra (2001) describes the management of natural resources and the environment for livelihoods and welfare based on three empirical studies in India, to show that the endowment of social capital may be measured by how well individuals cooperate across the traditional division of institutions (state, market and nonmarket). Berke and Folke (1998) look at management practices based on local ecological knowledge and offer the following guiding principles for designing management systems that build resilience in social–ecological systems: (1) ‘flow with nature’, (2) enable the development and use of local ecological knowledge to understand local ecosystems, (3) promote self-organization and institutional learning and (4) develop values consistent with resilient and sustainable social–ecological systems.

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Nested forest tenure systems, fisheries and joint farming–forestry systems help to determine the function of linkages. Mexican resource tenure systems function as ‘shells’ that provide the super-structure within which activities are developed and operate (Alcorn and Toledo, 1995). Such shells are linked in very specific ways to the larger ‘operating system’ in which the shell is embedded. The best course of action for promoting ecologically sustainable resource management is to support existing structures. Hammer (1995) focuses on the links between ecological and social systems in Swedish fisheries, especially in the Baltic Sea. He compares traditional small-scale and current large-scale management systems in terms of how they promote linkages between social and ecological systems, and finds that large-scale systems are more vulnerable because of their failure to process ecosystem feedbacks. Social–ecological linkages help to analyse the broader parametric effects of fishing on the whole biotic and environmental system (Wilson and Dickie, 1995). The fundamental cause of overfishing lies in the social institutions that either cannot grasp the complexities of biological interactions, or have insufficient means to control the inputs. This institutional difficulty, combined with the uncertainty characterizing marine systems, suggest the appropriateness of a multilevel governance system that captures the social–ecological linkages on different scales. Pradhan and Parks (1995) look at how the interactions between forests and subsistence agricultural systems in Nepal’s villages are influenced by the activities of rural farming communities that depend on the forest for various subsistence products. Past government efforts to protect forest resources by excluding local communities have resulted in the opposite effect. Destruction of the social–ecological linkages at the local level has resulted in village residents perceiving forests as open-access resources, and this has led to further environmental degradation. Sastry (2005) examines the spatial dimensions of making development more sustainable in the mountainous Western Ghats region of India, from the economic, social and environmental perspectives. He proposes an integrated model, which promotes three distinct forest ecosystems to operate at three different altitudes where three separate socioeconomic systems operate. The model helps to rejuvenate forests while maintaining ecological balance – based on the ‘unity in diversity’ approach. Satake and Iwasa (2006) use a Markov model of social–ecological coupling to show that myopic decisions by private landowners will push entire landscapes toward agricultural use, although the forested state is more socially optimal. A long-run management view and enhanced forest recovery is the remedy.

4.2.6 Poverty, population and natural-resource use Linkages among poverty, population and natural-resource use are discussed here in the context of property rights. A broader discussion is provided in Section 2.3.5. The population policy literature reflects the current view that previous successes in family planning, directed at the supply side of population growth, cannot be sustained without paying serious attention to reducing both the demand for births and the momentum of population growth (Bongaarts, 1994). Proposed policies include establishing formalized systems of property rights to


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resources, education of women to enhance economic standing and incentives to postpone child-bearing to later years (Bongaarts, 1994; De Soto, 1993). Dasgupta (1995) finds that population growth is, in varying degrees, linked to poverty, to gender inequalities in the exercise of power, to communal sharing of child-rearing and to an erosion of the local environmental-resource base. These linkages suggest that population policy should contain, not only measures such as family planning programmes, improved female education and employment opportunities, but also other measures to alleviate poverty and provide basic household needs. Jodha (1995) shows how poverty affects resource-use behaviour based on desperation. He argues that the current unsustainable pattern of resource use in the Himalayas is due to the replacement of traditional conservation-oriented resource-management systems with more recent extractive systems. He examines the driving forces underlying this shift and discusses ways to restore some of the beneficial properties of the traditional systems. Munasinghe (1997) shows that oversimplifying the complexities of the poverty– population–resource-use linkage could lead to inequitable and unwarranted conclusions. He argues that, under appropriate circumstances, people may be considered a social resource that would complement and strengthen the natural-resource base, so enhancing economic prosperity – see Section 2.3.5. Grima et al. (2003) examine agricultural practices in fragile lands and hill areas in order to understand better the trade-offs among development, poverty alleviation and sustainable use of natural capital.

4.2.7 Lessons learned and conclusions Both general principles and specific social and ecological context play a crucial role in the design, implementation and maintenance of property rights regimes for environmental resources. Governance systems General principles of governance were discussed in relation to matching the scale and complexity of ecological systems with property rights regimes, ensuring that sets of rules are consistent across different levels of authority, distributing authority to achieve representation and contain transactions costs and coordinaing between jurisdictions. Specific properties of governance were presented for limiting air pollution, managing a fishery and enforcing regional environmental regulations. Equity, stewardship and environmental resilience General principles were discussed in terms of the relationship between equity, stewardship, environmental resilience and efficiency in property rights regimes designed for a range of environmental resources. Specific interactions were analysed in the contexts of traditional systems for maintaining biodiversity in India, changing property rights to national parks in Poland and mangrove–shrimp production systems in coastal Ecuador.

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Traditional knowledge General principles of traditional knowledge were discussed in terms of the interaction between international environmental policy on the use of traditional knowledge and the implementation of local-level resource-management systems that use traditional knowledge. Specific properties of traditional knowledge were presented in the contexts of practical knowledge about fishing in Iceland and Canada and the restoration of Maori property rights in New Zealand. Mechanisms linking humans and environmental resources General principles of mechanisms that link humans to their environment were discussed in terms of their structures and the processes by which they allow humans to observe environmental change, adapt their behaviour to reflect environmental change and create knowledge in the process. Specific properties of linking mechanisms were presented in the contexts of forest tenure systems in Mexico, fisheries management in Sweden and elsewhere and the interaction between agriculture and forestry in Nepal. Poverty, population and natural-resource use General principles of the connection between population and poverty were discussed in terms of the intermediate linkages of gender equality, child-rearing practices, women’s education and general employment opportunities. Specific properties of the population– poverty connection were presented in the context of the relationship of population growth to poverty and unsustainable forest use. Simple generalizations may lead to wrong conclusions because the poverty–population–resource-use nexus is complex. The diverse papers discussed in this section are woven together by a common thread – the interaction of social and ecological systems through property rights to produce environmental outcomes. They show how the ecological context shapes human organization and behaviour, and how the human context in turn shapes ecological organization and response. The structure of governance, values of equity and stewardship, traditional knowledge, linking mechanisms and conditions of poverty and population all form a part of that context. The analysis of property rights regimes confirms that the co-evolutionary path that humans and their environment follow (see Section 2.3) is indeed determined by the interaction of socioeconomic and ecological contextual elements.

4.3 Environmental and social assessment Sustainable development assessment (SDA) used in the project cycle includes economic, social and environmental elements (see Chapter 2). Economic (and financial) assessment relies on cost–benefit analysis (CBA) – see Sections 2.4.2 and 3.2.1. Below, we examine the other two key components of SDA: environmental and social assessment (EA and SA).


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4.3.1 Environmental assessment Most nations and donor agencies now incorporate EA into their decision making. EA process The EA process is a part of the SDA to ensure that development options under consideration are environmentally sound and sustainable and that any environmental consequences are taken into account early in project design. In recent decades, EA has been adopted by most countries and international agencies, and it has evolved into a comprehensive instrument for making development more sustainable. The breadth, depth and type of analysis in an EA depend on the nature, scale and environmental impacts. The process (a) evaluates the potential environmental risk and impacts of a project in its area of influence; (b) examines project alternatives; (c) identifies ways of improving project selection, siting, planning, design and implementation by minimizing, mitigating or compensating for adverse environmental impacts, as well as by enhancing positive impacts; and (d) follows up on managing environmental impacts during project implementation (World Bank, 1998). EA examines the natural environment (air, water and land); human health and safety; social aspects (involuntary resettlement, indigenous peoples and cultural property); and transboundary and global environmental aspects, in an integrated way. It also takes into account the variations in project and country conditions; the findings of country environmental studies; national environmental action plans; the country’s overall policy framework, national legislation and institutional capabilities related to environment and social aspects; and obligations of the country under relevant international environmental treaties and agreements. An EA should be initiated as early as possible in the project processing and should be integrated closely with the economic, financial, institutional, social and technical analyses of a proposed project (see Box 3.1). EA is most effective when preliminary findings are made available early in the preparation process. At that time, environmentally desirable alternatives (sites, technologies, etc.) may be considered, and implementation and operating plans can be designed to respond to critical environmental issues in a cost-effective manner. Later actions, such as making a major design change, selecting an alternative proposal or deciding not to proceed at all with a project, can become very expensive. Even more costly are delays in implementation of a project because of environmental issues that were not considered during the design stage. A range of instruments can be used to supplement the EA requirement: an environmental audit, strategic environmental assessment (SEA), hazard or risk assessment, and an environmental management plan (EMP). Other complementary approaches, such as environmentalcost accounting and life-cycle assessment, are used mainly in the private sector. EA procedures may also be applied to development activities broader than specific projects – e.g. an SEA can be adapted to regional or sectoral scales and used to assess impacts of sector-wide programmes, multiple projects or development policies and plans. A regional or sectoral EA can reduce the time and effort required for many project-specific EAs by

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identifying issues and existing data in advance, or by eliminating the need for a projectspecific EA. The process involves an analysis of the likely effects of a project or policy on the environment, recording these effects in a report, undertaking a public consultation exercise on the report, taking into account the comments on the report when making the final decision and informing the public about that decision. The EA implementation plan should provide for frequent coordination meetings and information exchange between EA and feasibility study teams. Most successful EAs have thorough mid-term reviews. Most major concerns arise within the first months, and the rest of the EA period focuses on mitigating measures. Implementation and supervision Supervision ensures that measures to mitigate anticipated environmental impacts, to monitor programmes, to correct unanticipated impacts and to comply with any environmental conditionalities, are implemented adequately. Procedures for startup and continuing operation of the project will normally specify these agreements as well as measures to protect the health and safety of staff. Proper staffing, staff training and procurement of spare parts and equipment to support preventive, predictive and corrective maintenance are also necessary elements of implementation. Supervision could be carried out through a combination of the following: (1) reports required on compliance with environmental conditionalities; status of mitigating measures, results of monitoring programmes and other environmental aspects of the project; (2) oversight by line agency with responsibility for the sector, and/or by environmental management, land use control, resource conservation or permit-issuing agencies at the local, regional or national level; (3) early warning about impending unforeseen impacts; (4) supervision missions to review implementation of environmental provisions, corrective actions taken to respond to impacts and compliance with environmental conditionalities, including institutional strengthening components; (5) site visits by environmental specialists or consultants as required to supervise complex environmental components or respond to environmental problems.

Reporting on the environmental aspects should cover key data (e.g. violations of pollution standards), descriptions of impacts observed, progress on mitigating measures, the status of monitoring programmes (especially those for detecting new impacts), progress on institutional strengthening and adherence to environmental conditionalities. At the conclusion of a project, a completion report is prepared and submitted, including a description of impacts that actually occurred, whether or not it was anticipated in the EA report, and evaluations of the effectiveness of mitigating measures and of institutional strengthening and training. The World Bank (1998) provides a checklist of major items. Environmental auditing Environmental audits have been developed as an instrument to analyse existing conditions at and around a specific site, the environmental risk it may cause, the environmental


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liabilities and the degree of compliance with environmental standards and legislation. Users of such information are the companies themselves, customers, commercial banks, other lending institutions, local and national governments and the general public. Environmental audits help to reduce environmental and public health risks and assist in improving environmental management. Environmental audits provide reliable environmental information on industries and other types of enterprises in response to increasing public concern over the quality of the environment and stricter environmental legislation. It can be viewed as a ‘snapshot’ of the environmental situation at a given site. Audits can provide important input to the EA’s analysis of baseline conditions, consideration of alternatives and development of a mitigation plan for the existing impacts. Criteria may be based on local, national or international environmental standards, national laws and regulations, permits and concessions, internal management system specifications, corporate standards or guidelines of organizations such as the World Bank (World Bank, 1995). The environmental audit primarily uses existing documentation of the institution being audited, interviews with managers and personnel and observation of practices at the facility. Spot checks, in the form of tests and samples, are often included in the audit to verify that a company is in compliance and that information provided by the company is correct. Strategic environmental assessment Strategic environmental assessment (SEA) is a promising approach to ensure that strategiclevel policy making takes account of sustainability principles (Wood and Djeddour, 1992). A number of countries have recently introduced elements of this approach, and more appear likely to do so. To date, however, practical experience with SEA of policies, plans and programmes is limited, with critical issues yet to be resolved, such as the proposed scope of the approach, its role and relationship to other policy instruments in decision making and the appropriateness of relying on the methods and procedures of project EAs. SEA overlaps with the analysis of economy-wide policies and the environment (see below). Wood and Djeddour (1992) review the advantages of introducing SEAs from two viewpoints: overcoming the limitations of conventional project EAs and promoting more integrated approaches for assessing and evaluating the sustainability of development policies, programmes and plans. Ecological and economic considerations must be treated on the same level and at the same time in decision making. To promote the sustainomics principle of making development more sustainable (MDMS), all development options and activities must be adjusted to and be consistent with the ‘carrying capacity’ of the global biosphere and regional ecosystems. Often, scientific understanding is inadequate to permit predictions of whether and when significant thresholds will be crossed (i.e. the point at which cumulative stress of use and activity will cause irreversible change or structural breakdown in natural systems; see Kay (1991)). SEA extends the principles of EA to cover the development policies and plans that govern the conversion and depletion of natural capital. This basic approach must be coordinated

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with other strategies and instruments for environment–economy integration, including analysis of links between economy-wide policies and the environment (see Chapters 3, 7, 8 and 9). SEA may be seen as a vector for incorporating sustainability. Specifically, this process can help to instill and integrate environmental goals and principles into the highest levels of policy making, ensure that economic and fiscal agencies are responsible and accountable for the environmental consequences of their choices and actions and promote long-term changes in attitudes and assumptions about economic growth. Economy-wide policies and the environment Since economy-wide policies (both macroeconomic and sectoral) have pervasive, powerful and long-lasting effects throughout a national economy, their environmental impacts need to be assessed. This is a complex exercise, described in Chapters 3 (see Section 3.7), 7, 8 and 9.

4.3.2 Social assessment Social assessment (SA) is an important element of SDA – see Section 2.4.2. SA focuses on people, who are both the reason and a resource for sustainable development. Culture, societies and organizations are the foundation on which development programmes rest. People’s varied needs, beliefs and expectations are factors which shape their response to development activities. In the past, these factors were often analysed separately, and some key issues were overlooked. The sustainomics framework recognizes that integrated, systematic social analysis can help ensure that projects are more sustainable and feasible within their social and institutional context. The sustainable development triangle in Figure 2.1 emphasizes that stakeholder participation in the selection and design of projects can improve decision making, strengthen ownership and include poor and disadvantaged groups. SAs first emerged in the 1970s as a means to assess the impacts on society of development schemes and projects before they went ahead. It has since been incorporated into the formal planning and approval processes in many countries, in order to assess how major schemes may affect population, groups and settlements (Barrow, 2000). IAIA (2003) states the following: ‘Social assessment includes the processes of analysing, monitoring and managing the intended and unintended social consequences, both positive and negative, of planned interventions (policies, programmes, plans, projects) and any social change processes invoked by those interventions. Its primary purpose is to bring about a more sustainable and equitable biophysical and human environment.’ SA provides a framework for incorporating participation and social analysis into the design and delivery of projects (World Bank, 1995). SAs are carried out in order to: (a) identify key stakeholders and facilitate participation in project selection, design, implementation and monitoring and evaluation; (b) ensure that project objectives and incentives are acceptable to all the people intended to benefit, and that social differences are taken into account in project design; (c) assess the social impact of investment projects, and determine


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how adverse impacts can be avoided, minimized or substantially mitigated, and positive impacts maximized; (d) develop capacity to enable participation, resolve conflict, permit service delivery and carry out socially sound mitigation measures; and (e) make projects more sustainable, whereby the right institutions are strengthened, constraints are overcome and micro–macro links are made. SAs may also be included in poverty assessments and other economic and sector studies; they involve consultations with stakeholders and affected groups and other forms of data collection and analysis. Formal studies need to be carried when social factors are complex and social impacts are significant. Where there is considerable uncertainty, due to lack of awareness, commitment or capacity, SAs can contribute to the design of projects that build on experience and are responsive to change. The degree of stakeholder involvement needed also influences assessment design. In some cases, stakeholders simply provide information and no further interaction is foreseen, but often projects are improved when issues are jointly assessed and agreed, or beneficiaries are given the responsibility for identifying problems and empowered to find solutions. Where local participation in project design and implementation is expected, participatory data collection and analysis can help build trust and mutual understanding early in the project cycle. Stakeholder analysis involves the identification of key stakeholders, interests, influence and power, liability and risks and plans for stakeholder participation. It is important that findings be discussed with affected people to ensure that conclusions and recommendations are appropriate. Many methodological tools can be used when conducting SAs, including quantitative surveys, qualitative methods, such as beneficiary assessment, and participatory processes and workshops (World Bank, 1996b). It is the task of the SA team to identify which concepts apply and what methods and tools should be used to provide decision makers with operationally relevant information.

Part II Global and transnational applications

5 Global analytical applications1

In this chapter, applications of key elements of the sustainomics framework are illustrated through several examples dealing with two critical global problems – climate change and sustainable development, and how they are best addressed together. Section 5.1 provides a general analysis of the circular linkages between these two issues. In Section 5.2, challenges posed to the social, economic and environmental dime\nsions of sustainable development, and relevant principles for formulating a policy response, are described. Ethical and equity considerations play an important role, especially in addressing the unfair and disproportionately large share of the burden imposed on the poor and vulnerable. Section 5.3 defines and analyses the principal potential human responses – adaptation and mitigation. Several practical applications are provided. Three international-level case studies are described in Section 5.4. First, alternative climate-change-mitigation response strategies are assessed in terms of the optimality and durability approaches. Next, we examine the interplay of equity and efficiency in joint implementation, as well as in emissions trading, especially between Annex 1 and non-Annex 1 countries. Sections 5.5 and 5.6 discuss how a global problem such as climate change might interact with sustainable development at the national level through a case study that examines greenhouse gas (GHG) mitigation prospects in Sri Lanka. National energy-sector responses are analysed, and a real options framework for carbon options trading under uncertainty is described.

5.1 Climate change and sustainable development Comprehensive assessments by the Intergovernmental Panel on Climate Change (IPCC, 2001a, b, c, d, 2007a, b, c, d) state that climate change is unequivocal and very likely caused by human activities. Changes in important climate variables, such as global average temperature, are driving changes in natural and managed ecosystems (see Box 5.1). Serious, and possibly irreversible, future impacts are projected for a broad set of socioeconomic scenarios. Climate-change-response options include, primarily, adaptation and mitigation. Adaptation

1

The valuable contributions of K. J. Arrow, W. Cline, C. Fernando, K. G. Maler, P. Meier, J. Stiglitz and R. Swart to this chapter are gratefully acknowledged. Some parts of the chapter are based on material adapted from Arrow et al. (1995b), Munasinghe (2000a, 2001a), Munasinghe, Meier and Fernando (2003) and Munasinghe and Swart (2005).

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Global and transnational applications

Box 5.1 Key IPCC findings on climate change (1) (2) (3) (4) (5) (6)

(7) (8)

(9)

(10) (11)

(12)

The global climate is changing and human actions are partly to blame. Many physical and biological systems have already been affected. Non-linear, large-scale and possibly irreversible changes in climate system components may occur, but probably not in this century. Poor people and poor countries are the most vulnerable to climate-change impacts because they have the lowest capacity to adapt. Inertia in both natural and socioeconomic systems requires a long time perspective and safety margins in designing climate responses. Many technological and biological options are known that can enable us to meet short-term emissions reduction targets (e.g. the Kyoto Protocol) and to stabilize long-term GHG concentrations. Additional measures related to changes in economic structure, institutional arrangements and behaviour can provide important opportunities to adapt to or mitigate climate change. There are many cultural, political, institutional, economic and technological barriers to the adoption of the various options, but also many types of policy instruments that can overcome these barriers. For most countries, mitigation costs will be less than a percentage point of projected annual macroeconomic growth rates, depending on how measures are combined and implemented. However, for particular sectors (e.g. energy-intensive industries) and countries (e.g. oilexporting countries), costs can be higher. For GHG emissions, the general socioeconomic pathways that countries will follow are as important as specific climate policies. While mitigation and adaptation options can be effective individually, it is better to integrate them into a sustainable development strategy that deals holistically with complex linked human and natural systems. Sustainable development can be mutually reinforcing with climate-change adaptation and mitigation at national, regional and local levels. Source: Munasinghe and Swart (2005).

involves measures that will reduce the impacts of climate change (without necessarily altering the probability that it will occur), whereas mitigation includes actions that will reduce the likelihood of climate change (e.g. by reducing GHG emissions or removing them from the atmosphere). Stern (2006) reviews economic issues in detail. Figure 5.1 shows an integrated assessment modelling (IAM) framework, including the full cycle of cause and effect between climate change and sustainable development (IPCC, 2001a). Each socioeconomic development path in the bottom right-hand quadrant (driven by the forces of population, economy, technology and governance) gives rise to different levels of GHG emissions (carbon dioxide, halocarbons, methane and nitrous oxide). These gases accumulate in the atmosphere, disturbing the natural balance between incident solar radiation and energy re-radiated from the Earth, as shown in the climate-domain box on the left-hand side. Such changes underlie the enhanced greenhouse effect that increases

5 Global analytical applications Sustainable development domain

climate-change stresses climate system

adaptation

Climate domain

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adaptive capacity

human and natural systems

feedback

econ. soc. envir.

non-climate stresses

radiative forcing

feedback

feedback

atmospheric GHG emission and concentration scenarios

feedback

human actions causing GHG emissions

mitigation

feedback mitigative capacity

different socioeconomic development paths

Figure 5.1. Circular interaction between climate change and sustainable development.

radiative forcing, which will change the climate well into the future and impose stresses on the human and natural systems shown in the top right-hand quadrant (sustainable development domain). Such impacts on human and natural systems will ultimately have effects on socioeconomic development paths, thus completing the cycle. The development paths also have direct effects on the natural systems in the form of non-climate stresses, such as changes in land use, leading to deforestation and land degradation. Development paths strongly affect the capacity to adapt to and mitigate climate change. The adaptive capacity (of both human and ecological systems) will enhance adaptation and reduce the severity of impacts. Analogously, superior mitigative capacity in human society could enhance prospects for future GHG mitigation. Thus, adaptation and mitigation response strategies are dynamically connected with changes in the climate system and the prospects for ecosystem adaptation, food production and long-term economic development. Finally, the sustainable development triangle (see Chapter 2) provides a useful framework for analysing the effects of climate change on future socioeconomic development scenarios. Feedback occurs throughout the cycle, and changes in one part affect other parts dynamically via multiple paths. Material- and energy-intensive lifestyles and continued high levels of consumption, as well as rapid population growth, are inconsistent with sustainable development paths. Further, extreme socioeconomic inequality within and between nations undermines the social cohesion that would promote sustainability and make policy responses more effective. Socioeconomic and technology policy decisions made for non-climate-related reasons have significant implications for climate-change impacts and policy, as well as for other

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environmental issues. In addition, vulnerability to climate-change impacts is directly connected to environmental, social and economic conditions, as well as to institutional capacity. Kok and de Coninck (2004) and Swart, Robinson and Cohen (2003) review options for broadening climate policy by linking it with sustainable development.

5.2 Applying the sustainomics framework to climate change The climate-change problem fits in quite readily within the broad conceptual framework of sustainomics described in Chapter 2. Responding to concerns of decision makers, the IPCC is analysing climate issues within the framework of the sustainable development triangle (IPCC, 2001d; Munasinghe, 2000a; Munasinghe and Swart, 2000). Relevant sustainomicsrelated principles that could be applied are outlined below.

5.2.1 Economic, social and environmental risks and opportunities Global warming poses a significant potential threat to the future economic well-being of most human beings. Both monetarily quantifiable and non-quantifiable costs arise from the impacts of climate change and the measures people take to mitigate and adapt to it. Basically, the efficient economic response will be to maximize the net benefits derived from the use of the global atmospheric resource (see Section 2.3.2). This implies that the stock of atmospheric assets, which provide a sink function for GHGs, needs to be maintained at an optimum target level, defined by the point where the marginal GHG abatement costs are equal to the marginal avoided damages (see Section 5.4.1). Climate change could also undermine social welfare and equity in an unprecedented manner. More attention needs to be paid to the vulnerability of social values and institutions, which are already stressed due to rapid technological changes (Adger, 1999). Especially within developing countries, erosion of social capital is undermining the basic glue that binds communities together – e.g. the rules and arrangements that align individual behaviour with collective goals (Banuri et al., 1994). Existing mechanisms to deal with transnational and global problems are fragile and unable to cope with worsening climate-change impacts – e.g. more ‘environmental’ refugees (Lonergan, 1993; Westing, 1992). Both intra- and intergenerational equity will be worsened, among and within countries, due to the uneven distribution of the costs of damage, as well as adaptation and mitigation efforts (Bruce et al., 1996); see Section 5.2.3. The poor are especially vulnerable to disasters (Banuri, 1998; Clarke and Munasinghe, 1995). Inequitable distributions are not only ethically unappealing, but also unsustainable in the long run (Burton, 1997). More generally, inequity undermines social cohesion and worsens conflicts over scarce resources. Historical evidence on large-scale disasters such as El Niño provides useful insights into future climate-change impacts. Food insecurity, exacerbated by rapid global trade expansion, combined with two massive El Niño droughts in the late nineteenth century, killed tens of millions in the developing world and set back their development for many decades (Davis, 2001); see Section 1.2.3. There are disturbing parallels today, with rapid globalization of

5 Global analytical applications

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commodity and financial markets and increasing risks to food supplies of the poor due to climate change (Munasinghe, 2001a). Yohe and Van Engel (2004) have analysed the potential trade-off between equity (measured by the convergence of per capita GDP between rich and poor countries) and sustainability (measured by the contraction in fossil-fuel consumption compared with current levels) over a 50-year horizon. They seek to resolve the conflict between sustainability and equity, by using the very transfers of international capital that would promote relative ‘income equity’ between rich and poor countries to facilitate ‘burden sharing’ equity – by spreading the cost of achieving any emissions reduction target more evenly across their boundaries. The environmental viewpoint draws attention to the fact that increasing anthropogenic emissions and accumulations of GHGs might significantly perturb a key global sub-system – the atmosphere (UNFCCC, 1993). Changes in the global climate (e.g. mean temperature, precipitation, etc.) could also threaten the stability of a range of critical, interlinked physical, ecological and social systems and sub-systems (Watson, Zinyowera and Moss, 1996). This view is related to the durability approach (see Section 2.3). Environmental sustainability (see Section 2.2.2) will depend on several factors, including (a) climate-change intensity (e.g. incidence of extreme events); (b) system vulnerability (e.g. exposure and sensitivity to climate impacts); and (c) system resilience (i.e. the ability to recover from impacts). On the more positive side, climate-change response also provides some opportunities for furthering sustainable development. The international acknowledgement of climate change as a risk for current and future generations has also highlighted the current vulnerability of populations and ecosystems to a broad range of existing environmental issues (of which climate change is only one); see Chapter 4. Reducing vulnerability of socioeconomic and ecological systems to climate change could also reduce their vulnerability to a broader set of unsustainable practices, improve resilience, increase the efficiency of resource use, reduce pressures on the environment and enhance human well-being. To summarize, climate change and sustainable development issues are best addressed together; for example, using the sustainomics principle of making development more sustainable (see Chapter 2).

5.2.2 Relevant principles for policy formulation When considering climate-change responses, several economic principles and ideas are useful, including the ‘polluter pays’ principle, economic valuation, internalization of externalities and property rights. The polluter pays principle argues that those who are responsible for damaging emissions should pay the corresponding costs. The market-based rationale is that this provides an incentive for polluters to reduce their emissions to optimal (i.e. economically efficient) levels. Quantification and economic valuation of potential damage from polluting emissions is a key prerequisite. The atmosphere is a common property resource, which GHG emitters can freely pollute without penalties. Such ‘externalities’ (defined in Section 3.2.2) need to be internalized by imposing costs on polluters

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that reflect the damage caused. Pigou (1932) originally defined and treated externalities in rigorous fashion. Here, the notion of property rights is also relevant to establish that the atmosphere is a valuable and scarce resource that cannot be used freely and indiscriminately. An important social principle is that climate change should not be allowed to worsen existing inequities – although climate-change policy cannot be expected to address all prevailing equity issues. Some special aspects include: (a) the establishment of an equitable and participative global framework for making and implementing collective decisions about climate change; (b) reducing the potential for social disruption and conflicts arising from climate-change impacts; and (c) protection of threatened cultures and preservation of cultural diversity. From the social equity viewpoint, the polluter pays principle is based not only on economic efficiency, but also on fairness. An extension of this idea is the principle of recompensing victims – ideally by using the revenues collected from polluters. There is also the ethical issue concerning the extent of the polluters’ obligation to compensate for past emissions. Weighting the benefits and costs of climate-change impacts according to the income levels of affected persons is also one way of redressing inequities (see Section 3.2.2). Equal per capita GHG emission rights (i.e. equal access to the atmosphere) is consistent with both conventional justice principles (Kverndokk, 1995) and the UN human rights declaration underlining the equality of all human beings. Traditional economic analysis has addressed efficiency and distributional issues separately – i.e. the maximization of net benefits is distinct from who might receive such gains (see Box 2.3). Equity aspects of climate change are discussed in Section 5.2.3. Several concepts from contemporary environmental and social analysis are relevant for developing climate-change-response options, including the concepts of durability, optimality, safe limits, carrying capacity, irreversibility, non-linear responses and the precautionary principle. Broadly speaking, durability and optimality are complementary and potentially convergent approaches (see Section 2.3). Under the durability criterion, an important goal would be to determine the safe limits for climate change, within which the resilience of global ecological and social systems would not be seriously threatened. In turn, the accumulations of GHGs in the atmosphere would have to be constrained to a point that prevented climate change from exceeding these safe margins (see Section 5.4.1). Some bio-geophysical and socioeconomic systems may respond to climate change in a non-linear fashion, with the potential for catastrophic collapse. Thus, the precautionary principle argues that lack of scientific certainty about climate-change effects should not become a basis for inaction, especially where relatively low-cost steps to mitigate climate change could be undertaken as a form of insurance (UNFCCC, 1993).

5.2.3 Equity, ethics and climate change Equity is an important element of the collective decision-making framework needed to respond to global climate change (see Box 5.2).


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Box 5.2 Why is equity important in climate change? Equity considerations are important in addressing global climate change for a number of reasons, including: (a) moral and ethical concerns; (b) effectiveness; (c) sustainable development; and (d) the UNFCCC itself. First, the principles of justice and fair play are important in human interactions. Most modern international agreements, including the UN Charter, enshrine moral and ethical concerns relating to the basic equality of all human beings and the existence of inalienable and fundamental human rights. Equity is also embodied, explicitly or implicitly, in many of the decision-making criteria used by policy makers. Second, equitable decisions carry greater legitimacy and encourage all parties to cooperate better in carrying out mutually agreed actions. A successful collective human response to climate change will require the sustained collaboration of all sovereign nation states and many billions of human beings over long periods of time. While penalties and safeguards have a role, decisions that are perceived as equitable will be implemented more willingly than those enforced under conditions of mistrust or coercion. Thus, a future scenario that restricts per capita carbon emissions in the South to 0.5 tonnes per year, while permitting a corresponding Northern level of over 3 tonnes, will not facilitate the cooperation of developing countries, and therefore is unlikely to be durable. Third, as explained earlier, equity and fairness are extremely important elements of the social dimension of sustainable development. Thus, the impetus for sustainable development provides another crucial reason for finding equitable solutions to the problem of global warming. Fourth, the UNFCCC has several specific references to equity in its substantive provisions. To begin with, Article 3.1 states that ‘The Parties should protect the climate system for the benefit of present and future generations of humankind, on the basis of equity and in accordance with their common but differentiated responsibilities and respective capabilities. Accordingly, the developed country Parties should take the lead in combating climate change and the adverse effects thereof.’ Other equity-related principles emphasized in Article 3 include: (a) the right to promote sustainable development; (b) the need to take into account the specific needs and special circumstances of developing-country and vulnerable parties; (c) the commitment to promote a supportive and open international economic system; and (d) the precautionary principle. According to Article 4.2 (a), all developed-country parties are required to take the lead in mitigating climate change. Further, they should transfer technology and financial resources to developing-country parties that are particularly vulnerable to the adverse effects of climate change in meeting the costs of adaptation (Article 4.4). Article 4.2 (a) also requires developed-country parties to commit themselves to ‘adopt national policies and take corresponding measures on the mitigation of climate change … These policies and measures will demonstrate that developed countries

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are taking the lead in modifying longer-term trends in anthropogenic emissions consistent with the objective of the Convention … taking into account the difference in the Parties’ starting points and approaches, economic structures, available technologies and other individual circumstances, as well as the need for equitable and appropriate contributions by each of the Parties to the global effort regarding that objective.’ Finally, Article 11.2 requires the Convention’s financial mechanism to ‘have an equitable and balanced representation of all Parties within a transparent system of governance’. The foregoing provisions of the UNFCCC provide important guidance on how equity considerations should influence or modify the achievement of the Convention’s goals. While protecting the climate system is a ‘common concern of humankind’, the Annex 1 countries are expected to take a lead in initiating actions and assume a greater share of the burden. Furthermore, in burden sharing, emphasis is also placed on applying equity considerations among developed countries. The responsibilities of the present generation with respect to those of future generations are also referred to. Finally, equity is mentioned in the context of governance, to emphasize the importance of including procedural elements that guarantee distributive outcomes that are perceived to be equitable.

Procedural and consequential equity The requirements of the UNFCCC indicate that equity principles must apply to: (a) procedural issues – how decisions are made and (b) consequential issues – the outcomes of those decisions. Both aspects are important because equitable procedures need not guarantee equitable decisions, and vice versa. Support for the convention and its implementation will depend largely on widespread participation by the global community and on how equitable it is perceived to be. Procedural equity has two components. First, equity implies that those who are affected by decisions should have some say in the making of these decisions, either through direct participation or representation. Second, the process must ensure equal treatment before the law – similar cases must be dealt with in a similar manner, and exceptions must be made on a principled basis. Consequential equity also has two elements, relating to the distribution of the costs and benefits of: (a) impacts and adaptation to climate change and (b) mitigating measures (including the allocation of future emissions rights). Both elements (a) and (b) have implications for burden sharing among and within countries (intragenerational and spatial distribution) and between present and future generations (intergenerational and temporal distribution). The equity of any specific outcome may be assessed in terms of a number of generic approaches, including parity, proportionality, priority, classical utilitarianism and Rawlsian distributive justice. Societies normally seek to achieve equity by balancing and combining several of these criteria. Self-interest also influences the selection of criteria and the determination of equitable decisions. Consequential equity as applied in the


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international arena is derived mainly from these principles, which were developed originally in the context of human interactions within specific societies. A human response to climate change requires the application of equity at an even more elevated (global) level, where there is far less practical experience. Cultural and societal norms and views about ethics, the environment and development complicate efforts to achieve a worldwide consensus (Pinguelli-Rosa and Munasinghe, 2002). Even the urgency of a response to climate change is subject to dispute. Given the different meanings, philosophical interpretations and policy approaches associated with equity, judgement plays an important role in resolving potential conflicts. Ultimately, any global response strategy will be a compromise between different views. As an example, the practical difficulties of allocating future emissions rights among nations are explored in a case study – see below (Munasinghe, 1998a). Nevertheless, from a pragmatic viewpoint, significant progress toward a global consensus would be made if the decision-making framework could harness enlightened self-interest to support equitable or ethical goals. Thus, developed countries will have a self-interest in shouldering the major burdens of addressing climate-change issues because their own citizens have shown greater willingness-to-pay to solve environmental problems. Similarly, developed nations would enjoy greater opportunities for trade and export if developing-country markets grew without being disrupted by climate change. All countries would also prefer to avoid the significant negative spillover effects of worldwide instability arising from climate change. At the same time, the higher risks and vulnerability faced by developing countries provides them with an incentive to seek common solutions to the climate-change problem. Equity and economic efficiency General problems of reconciling equity and economic efficiency were discussed earlier (see Box 2.4). In the specific context of climate change, the lack of proper institutions to make equity-related assessments and play a redistributive role on an international scale compounds the problems of comparing national welfare levels across countries. The extreme viewpoints are that: (a) welfare levels should be compared as though all countries value each others’ welfare equally (i.e. equivalent welfare functions exist across countries and equal weights might be assigned to each) and (b) that each country is concerned primarily with its own welfare and bears no responsibility for the welfare of any other. Since GHG emissions in one country affect others, a convention on climate change must arrive at some compromise between these two extremes. Intragenerational (spatial) equity While equity is not synonymous with equality, differences between countries clearly affect issues of international equity. International response strategies will eventually translate into actions adopted at the national level, and therefore should reflect equity concerns within countries as well. Several categories of differences between countries that are relevant to the question of equity are discussed next.

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Wealth and consumption Wealth is perhaps the most obvious and prevalent difference between (and within) countries. Measured in terms of GNP, the World Bank estimates that about 2.4 billion of the world’s population (41%) live in low-income countries (World Bank, 2001). These countries have an average per capita GNP of $420. In contrast, 15% of the world’s population live in ‘highincome economies’, which have an average per capita GNP of $26 440. The remaining 44% of the population live in the ‘middle-income economies’ and ‘low- and middle-income economies’, which have an average per capita GNP of $1500. Such wide variations in per capita income between countries imply that simply comparing this measure of welfare may be inappropriate (see Chapter 2). These differences have direct implications for the way climate change is addressed. For instance, activities in developing countries that produce GHGs are generally related to fulfilling ‘basic needs’. They may result from generating energy for cooking or keeping tolerably warm, engaging in agricultural practices, consuming energy to provide barely adequate lighting and occasionally for travel by public transport. In contrast, emission of GHGs in developed countries is likely to result from activities such as operating personal vehicles and central heating or cooling and energy embodied in a wide variety of manufactured goods and the use of such goods. Therefore, the level of personal wealth is directly related to the welfare impacts of reducing GHG emissions (WCED, 1987). Furthermore, wealth has a direct bearing on the vulnerability to the impacts of climate change. By virtue of being richer, some countries will be able to adapt more effectively to climate change. A similar relationship between poor and rich also exists within countries. Poorer countries are less prepared to adopt mitigation and adaptation strategies due to several reasons. First, poverty has implications for urgency of other national priorities and of time scales used in policy planning. Wealth has a direct correlation to personal discount rates (i.e. discount rates decline with rising wealth). The more affluent have a greater share of disposable wealth to invest in the future, and therefore are able to conceptualize longer planning time horizons. The poor are forced to focus on shorter-term objectives, such as basic survival necessities. A similar phenomenon applies to national-level economic and political systems. Consequently, interest rates are higher in poorer countries, capital is scarcer and the emphasis of policy planning is on the short-term needs, such as poverty alleviation and employment generation. The focus of government may be to keep up with infrastructure needs due to rapidly rising demands. They may not have the luxury to consider optimal development strategies, as some richer countries may be able to. Thus, national wealth affects both actual investment decisions as well as broader public policy planning capability. The IPCC Special Report on Developing Countries addresses this concern by stating that ‘the priority for the alleviation of poverty continues to be an overriding concern of the developing countries; they would rather conserve their financial and technical resources for tackling their immediate economic problems than make investments to avert a global problem which may manifest itself after two generations’. Similarly, Article 4.7 of the


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UNFCCC states that ‘economic and social development and poverty eradication are the first and overriding priorities of the developing country Parties’, and thus their climate change responses will be influenced by these considerations. Even though concerns about climate change will grow in the developing countries (especially the most vulnerable), they are likely to lack the resources to address the issue. Contributions to climate change Given the range of sources and sinks, different ways of aggregating and presenting data can have implications for equity. The developed countries accounted for over 85% of cumulative worldwide GHG emissions up to 1990. On a per capita basis, the contrasts are even more stark, with North America and all developed countries, respectively, emitting over 20 times and 11 times the total cumulative carbon dioxide emissions of the developing countries. Thus, some authors have argued that the industrialized countries owe the developing world a ‘carbon debt’, due to disproportionately high GHG emissions in the past (Jenkins, 1996; Munasinghe, 1993a). The developing countries also need considerable ‘headroom’ to allow for the future economic growth and energy consumption, since they are starting from a much lower base (see Box 3.1). Meanwhile, differentiating along the lines of developed and developing countries may be too simple, because they vary. Winkler, Brouns and Kartha (2006) have assigned mitigation burdens and financial transfers among non-Annex 1 countries, based on responsibility for climate change, capability and potential to mitigate. Incidence of impacts and vulnerability The incidence of impacts may bear no relationship to the pattern of GHG emissions, which violates equity principles and is inconsistent with the ‘polluter pays’ and ‘victim is recompensed’ approach. In particular, the negative effects of climate change are likely to be most pronounced in tropical regions, where developing countries lie. In addition to asymmetries in incidence, many developing countries are more vulnerable to the effects of global warming because of fewer resources, weaker institutional capacity and scarcer skilled human resources. The plight of poor and subsistence-level communities, or low-lying small island nations subject to sea-level rise, will be quite bleak. Therefore, such groups need special attention, based on humanitarian and equity principles and procedures already established to deal with disasters (see Chapter 16). Equity within countries Most of the above arguments relating to equity across countries also apply to equity within individual nations. Fortunately, there are many existing mechanisms within countries (such as subsidized food, healthcare and schooling, social security or progressive taxation) to achieve a fairer redistribution of resources. Equity issues, especially views about social justice, will influence the formation, decisions and credibility of such policies. Although the capacity and legitimacy of these institutions may vary, they provide a useful framework within which climate-change issues can begin to be addressed at the national and subnational levels.

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Intergenerational (temporal) equity and discounting Most of the earlier points relating to spatial equity also affect equity across time, and in very similar ways. First, future generations may be richer or poorer than the present generation. Second, past and present human actions will determine future climate-change impacts. Third, while future generations will have to bear the consequences of past GHG emissions, they will also benefit from sacrifices and investments made by their forbears. At the same time, it is unclear whether our descendants will be more or less vulnerable to climate-change impacts. There are two additional issues relating to intergenerational equity. First, to the extent that future generations are not represented in the ongoing decision-making process that will affect climate change, particular care needs to be exercised to protect their rights. Second, once events unfold, it will be difficult to compensate future generations for past mistakes. Once again, extra prudence is required to avoid imposing future burdens that are both irreversible and impossible to compensate. Nevertheless, generations do overlap in practice (e.g. parents and children) and will facilitate the incorporation of some intergenerational concerns into the discount rate and decision making in general. Social rate of discount From an economic viewpoint, one of the principle instruments available to influence the allocation of resources across time is the social rate of discount (see Section 3.6). Indeed, the conclusions derived from any long-term analysis of climate-change policy will depend crucially on the discount rate that is selected – i.e. the real discount rate, net of inflation. The conceptual mirror image of the discount rate (at which future expenditures are discounted to the present) is the interest rate (at which present-day capital will grow into the future). Since discounting compares economic costs and benefits that occur at different times, it will have a direct bearing on intergenerational equity. In climate-change analysis, the effects of discounting will be pronounced for two reasons: (a) the relevant time horizons are extremely long and (b) many of the costs of mitigation occur relatively early, while potential benefits lie in the distant future. Lower, present-day discount rates favour future generations by increasing the importance of future benefits (of avoided harm), relative to near-term costs (of mitigation). The two main approaches to determining a value for the social rate of discount are based on the consumer rate of time preference (CTP), and the (risk-free) marginal returns to investment (MRI) – see Box 3.2. While the concepts underlying these two approaches may appear to diverge, in practice both the CTP and MRI produce comparable estimates for the social rate of discount. Thus, estimates for the CTP vary from 1 to 4% and for the MRI from 3 to 6% per annum (Arrow et al., 1995b). Climate change negotiations, ethics and equity Equity and ethical considerations will play an important role in determining an effective climate-change response strategy. Ongoing climate-change negotiations are based on several factors, including risk, fear and the precautionary principle. Current approaches favour


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mitigation efforts via a global market that is driven by profits derived from trading in emission reductions, rather than through more deep rooted alterations in social attitudes – as suggested in the sustainomics vision (see Section 1.2.4). Many climate-change initiatives were undertaken in both the public and private sectors, ahead of the ratification of the Kyoto Protocol. Some of them exemplify the speculative nature of global climate issues and clearly reflect the motivations of stakeholders striving to acquire future economic advantages through dealing in GHG emissions. The brokering of carbon credits over the Internet is one example of current pressures driving emissionsreduction mechanisms in the international marketplace. The Prototype Carbon Fund (PCF) run by the World Bank is the semi-government version of such trading in carbon credits, influencing emerging criteria for certification projects. The International Emissions Trading Association (IETA) further exemplifies the involvement of leading world enterprises using market-based efforts to reduce emissions in the oil and power sectors. It seems easier and cheaper to speculate on mitigation projects relating to land use (forestry, agriculture, etc.) than to invest in new energy sources or effective alterations in lifestyles and consumption standards that will reduce GHG emissions. Climate-change negotiations are strongly influenced by the capacity and potential of countries to articulate their viewpoints. The developing countries are especially handicapped in this regard. The sustainomics approach suggests that they would be able to place themselves in a more favourable position in these global talks by focusing on the linkages among climate change, poverty and sustainable development and by clearly explaining the strategic and sociopolitical importance of the more humanistic aspects, such as equity and ethics. A recent book sets out the views of several experts with diverse disciplinary, sectoral and geographic backgrounds, on six relevant issues: economics, morality, politics, rights and law, philosophy and science (Pinguelli-Rosa and Munasinghe, 2002). Miguez (2002) argues that the largest share of historical and current global GHG emissions has originated in industrial countries. Per capita emissions in developing countries are still relatively low, and must grow to meet their future social and development needs. The Brazilian Proposal emphasizes the very deep gap between Annex I and nonAnnex I countries with respect to the atmospheric concentration of GHGs, rather than their emissions. The appropriate variable to measure climate change is the change in global mean surface temperature. Full support must be given to the least-developed countries to adapt to climate change. Estrada-Oyuela (2002) stresses that ethics and equity require common but differentiated responsibility among countries. To stabilize GHG concentrations, industrialized countries will have to reduce their emissions, while developing countries are permitted to increase emissions. The high cost of mitigation in Annex I countries decreases the possibility of equalizing per capita emissions among all nations. The main question then is How does the burden of emission reduction compare with other internationally imposed burdens? Market prices that distort real values are the cause of frequent assertions about lower emissionreduction costs in developing countries. Emission reductions would be more effective if the production volume of sectors and their projections were considered. The mechanism

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recognizes the specific needs of each country, while being equitable for both industrialized and developing countries. Banuri and Spanger-Siegfried (2002) point out that, while equity appears strongly as a foundational principle of the UNFCCC, it has gradually taken a back seat to considerations of cost-effectiveness and efficiency, as set out in the Kyoto Protocol. A long-term perspective should ensure that developing countries are able to grow economically and eradicate poverty. In the short run, this means identifying win–win policies, providing financial and technical assistance, and helping poor and vulnerable communities. If long-term capacity building for carbon-free growth is not fostered now, future mitigation costs will harm poor countries and deepen inequities. To ensure equity in mitigation, it is necessary to stimulate developing-country mitigative capacity. Clean development mechanism (CDM) projects that align equity and efficiency concerns help to make development more sustainable. Muylaert and Pinguelli-Rosa (2002) critically contrast the emphasis on ethics and equity in approaches used by the environmental community with the low priority accorded to these issues in approaches based on ‘power-politics’. They argue that ‘ethics’ may be understood better in terms of conduct – as behaviour without previous moral linkages. From this viewpoint, everyone has the power to decide what is fair, or not, and to negotiate the outcome on a case-by-case basis, depending on time and circumstances. Equity is not defined in the documents of the UNFCCC or the IPCC, and there is no formal requirement to implement this concept under international agreements on climate change. Since climatechange issues cannot be addressed without considering equity, the authors propose a more quantitative ‘equity index’. Ott and Sachs (2002) discuss important aspects of emissions trading. Under the UNFCCC, developed countries are requested to take the lead in combating climate change. Meanwhile, the CDM would assist developing countries financially and technologically in dealing with climate change. It should focus strictly on assisting non-Annex I countries in the transition to a non-carbon economy. Under such a scheme, only carbon-free energy, such as solar, biomass, wind and hydro, would be promoted by the CDM.

5.3 Climate-change adaptation and mitigation 5.3.1 Sustainable development and adaptation to climate change Adaptation refers to the adjustments in human and natural systems as a response to climatechange stresses and their effects, which moderate damage and exploit opportunities for benefit (e.g. building higher sea walls or developing drought- and salt-resistant crops). Different types of adaptation include anticipatory versus reactive adaptation, private versus public adaptation and autonomous versus planned adaptation. Clearly, sustainable development and adaptation to climate change are interlinked. Most sustainable development strategies are unrelated to climate change, but they could make adaptation more successful. Similarly, many climate-change-adaptation policies could make development more sustainable.


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Vulnerability, resilience and adaptive capacity Durability criteria or constraints focus on maintaining the quality and quantity of asset stocks (see Chapter 2). The various forms of capital are a bulwark that decreases vulnerability to climate change and reduces irreversible harm, rather than mere accumulations of assets that produce economic outputs. System resilience, vigour, organization and ability to adapt will depend dynamically on the capital endowment and magnitude and rate of change of a shock. In the context of climate change, vulnerability is the extent to which human and natural systems are susceptible to, or unable to cope with, the adverse effects of climate change (IPCC, 2001a, 2007b). It is a function of the character, magnitude and rate of climate variation, as well as the sensitivity and adaptive capacity of the system concerned. Resilience is the degree of change a system can undergo, without changing state. Adaptive capacity is the ability of a system to adjust to climate change. Strengthening adaptive capacity is a key policy option, especially for vulnerable and disadvantaged groups. Adaptive capacity itself will depend on the availability and distribution of economic, natural, social and human resources; institutional structure and decision-making processes; information, public awareness and perceptions; menu of technology and policy options; ability to spread risk, etc. (Yohe and Tol, 2001). These variables are linked to location-specific patterns of socioeconomic and social development. Adaptation options Adapting to climate change can be spontaneous or planned. Planning is needed to minimize the costs of negative impacts and maximize the benefits of positive impacts. Adaptation efforts must be combined with mitigation, since controlling of emissions is vital to minimize future impacts. The most vulnerable ecological and socioeconomic systems are those with the greatest sensitivity, the greatest exposure and the least ability to adapt to climate change. Ecosystems already under stress are particularly vulnerable. Social and economic systems tend to be more vulnerable in developing countries with weaker institutions and economies (e.g. high population density and low-lying coastal, flood prone and arid areas). Strategies for adapting to climate change include preventing losses (e.g. barriers against sea-level rise); reducing losses (e.g. changing the crop mix); spreading or sharing losses (e.g. government disaster relief); changing land use (e.g. relocating away from steep slopes) or restoring a site (e.g. historical monument prone to flood damage). Better strategies need advances in technology, management and law, finance and economics, public education, training and research and institutional changes. Incorporating climate-change concerns into development plans can help ensure that new investments in infrastructure reflect likely future conditions. While uncertainty complicates the crafting of adaptation policies, many such policies will make development more sustainable (e.g. by improving naturalresource management or social conditions). Recent work has focused on formulating and assessing such adaptation strategies (Corfee-Morlot, Berg and Caspary, 2002; Niang-Diop and Bosch, 2004).

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5.3.2 Sustainable development and mitigation of climate change Sustainable development and mitigation are also interlinked. Most sustainable development strategies are unrelated to climate change, but they could make mitigation more successful. Similarly, many climate-change mitigation policies could make development more sustainable. The IPCC recently elaborated six different reference scenarios that show a wide variety of alternative development pathways over the next century, each yielding a very different pattern of GHG emissions (IPCC, 2000). Lower-emission scenarios require less carbonintensive energy-resource development than in the past. Emission-reduction technologies have developed faster than anticipated. Improved methods of land use (especially forests) offer significant potential for carbon sequestration. Such methods might allow time for more effective mitigation techniques to be developed. Ultimately, mitigation options will depend on differences in the distribution of natural, technological and financial resources, as well as mitigation costs across nations and generations (IPCC, 2001c, 2007c). Although future low-emission paths will vary by country, the IPCC results indicate that appropriate socioeconomic changes combined with known mitigation technology and policy options could help to achieve atmospheric CO2 stabilization levels around 550 ppmv, or less, by 2100. Mitigative capacity The effectiveness of future mitigation could be improved by strengthening mitigative capacity (i.e. the ability to reduce GHG emissions or enhance sinks), which depends on social, political and economic structures and conditions. More research and analytic capacity is needed to build mitigative capacity in developing countries. Increases in mitigative capacity could allow climate-change considerations to be more effectively integrated with broader sustainable development strategy in a manner that effectively limits GHG emissions over time, while maximizing the developmental co-benefits of mitigative actions. Social learning and innovation, and changes in institutional structure, could strengthen mitigative capacity. Policy options that yield ‘no-regrets’ outcomes will help to reduce GHG emissions at no or negative social cost. However, the incremental costs of stabilizing almospheric CO2 concentrations over the next century rise sharply as the target concentration level falls from 750 ppmv to 450 ppmv. There are many technical, social, behavioural, cultural, political, economic and institutional barriers to implementing mitigation options within countries. Mitigation options Like adaptation, mitigation has cost and benefits. Many variables need to be considered in the cost equation, including: (a) internationally agreed timetables and targets for emissions reductions; (b) global population and economic trends; (c) development of new technologies; (d) rate of capital replacement; (e) discount rates; (f) co-benefits of mitigation actions that address non-climate issues; and (g) actions of industry and consumers in response to climate-change-related policy.


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Policies to minimize the risk by reducing GHG emissions will also come with a price tag and vary widely due to uncertainty. Although immediate action may seem more expensive, delays could lead to greater risks and therefore greater long-term costs. An early effort toward controlling emissions would increase the long-term flexibility of human responses to work toward stabilizing atmospheric GHG concentrations. Many cost-effective technologies and policies are available (e.g. hybrid engine cars, wind turbines, advances in fuel cell technology, end-use energy efficiency in building, transport, manufacturing and industry to reduce emissions, etc.), which not only mitigate GHG emissions, but also address other development objectives by increasing resource efficiency and decreasing environmental pressure. Governments need to promote these solutions actively, by addressing institutional and other barriers first. Economic incentives can be used to influence investors and consumers. For example, deposit funds could encourage people to trade in their cars and appliances for more energy-efficient models; manufacturers could be rewarded for selling climate-friendly goods, or penalized if they do not. Prices could incorporate climatechange concerns by changing taxes or subsidies. For example, a tax on oil, coal or gas would discourage fossil-fuel use and help reduce CO2 emissions. Tradable emission permits could also offer a cost-efficient, market-driven approach to controlling emissions. Caspary and O’Connor (2002) provide a useful review of such options. Energy policy is a key to enhancing the cost-effectiveness of decreasing emissions (e.g. optimal energy mix). Incentives for investing in cost-effective and energy-efficient technologies are essential, e.g. improved building design, new chemicals for refrigeration and insulation, more efficient refrigerators and cooling/heating systems. Power plant emissions of both air pollutants and GHG will fall if renewable sources are used. Technology innovation, energy efficiency and more renewable energy will be essential to stabilize GHG concentrations in the next 50–100 years, while also providing other co-benefits. Governments need to remove barriers that slow the spread of low-emission technologies. The transport sector is the most rapidly growing source of GHG emissions in most countries (see Chapter 11). Heavy reliance on fossil fuels makes controlling GHG emissions particularly difficult. In urban areas air pollutants, such as particulate matter and ozone precursors, also cause problems. New technologies can increase the efficiency of automobiles and reduce the emissions per kilometre travelled. Switching to less-carbon-intensive fuels will reduce local and regional air pollution, which is of serious concern in most cities in the developing world as well as in industrialized countries, but it will also help reduce carbon emissions (e.g. biofuels, fuel-cell-powered vehicles, etc.). Some policies to reduce emissions from transport include: (a) use of renewable energy technologies; (b) better maintenance and operating practices; (c) policies to reduce traffic congestion; (d) urban planners to encourage low-emission transport (e.g trams and trains, bicycles, walking); and (e) imposing user fees. Climate-friendly transport policies can promote development while minimizing the local costs of traffic congestion, road accidents and air pollution. Deforestation and agriculture account for increases in local and regional air pollution as well as GHG emissions. Forests need to be protected and better managed (see Chapter 13). Deforestation may be controlled by decreasing pressures of agriculture on forestry, slowing

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down population growth, involving local people in sustainable forest management, harvesting commercial timber sustainably and reducing migration into forest areas. Sustainable forest management can generate renewable biomass as a substitute for fossil fuels. Improved management to increase agricultural productivity could enable soils to absorb more carbon, at the same time leading to higher organic-matter content and enhanced productivity. Methane emissions from livestock could be reduced with new feed mixtures that improve the efficiency of digestion and also increase the overall efficiency of livestock management. Methane emissions from wet rice cultivation can be reduced significantly through changes in irrigation practices and fertilizer use, while improving or safeguarding current productivity and reducing environmental pressures. Nitrous oxides from agriculture can be minimized with new fertilizers and practices, some of which not only reduce nitrous oxide emissions, but also reduce nitrogen losses (in the form of polluting nitrates, nitrogen oxides and ammonia) and enhance fertilizer efficiency. Thus, it is possible to decrease emissions while generating environmental and economic benefits. ‘No-regrets’ emissions-reduction strategies are most effective in minimizing the costs of climate-change policies. Their benefits exceed costs, even excluding the benefits of avoided climate change, e.g. removing market imperfections like fossil-fuel subsidies or generating double dividends by using tax revenues to reduce other distortionary taxes. Public participation (i.e. by stakeholders, individuals, communities, businesses) is important for effective policies. Education and training is also vital (e.g. the importance of conserving energy, introducing building codes to maximize sunlight and use solar power, etc.). Equity aspects of policy need to be considered (i.e. cost-efficiency and fairness). Climate-change responses should aim to combine mitigation and adaptation. Developing country researchers have reiterated that development will remain the first priority while mitigation needs to pursued in this context (Munasinghe and Swart, 2005; Winkler et al., 2002). Coordinated actions across countries and sectors could reduce mitigation costs and limit concerns about competitiveness, conflicts over international trade regulations and carbon leakage. To summarize, early actions, including mitigation measures, technology development and better scientific knowledge about climate change, will increase the possibilities for stabilizing atmospheric GHG concentrations and make development more sustainable.

5.4 Global-level interactions between climate change and sustainable development Three simplified examples are presented below, to illustrate the application of some of the sustainomics-based concepts discussed earlier.

5.4.1 The interplay of optimality and durability in determining appropriate global GHG-emission target levels Optimal and durable approaches can help to determine target GHG-emission levels (Munasinghe, 1998a). Using economic optimization, the ideal solution is to estimate the


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costs / benefits

MAC

MAD ROP

GHG-emission reduction (a)

excessive abatement costs

MAC

costs / benefits

acceptable abatement costs

RAM

GHG-emission reduction

costs / benefits

(b)

zone of unacceptable risk

zone of acceptable risk

RAS

GHG-emission reduction

(c)

Figure 5.2. Setting mitigation targets: (a) cost–benefit optimum; (b) affordable safe minimum standard; (c) absolute standard.

long-run marginal abatement costs (MACs) and the marginal avoided damages (MADs) associated with different GHG-emission profiles – see Figure 5.2(a), where the error bars on the curves indicate measurement uncertainties (Bruce et al., 1996). The optimal emission levels would lie at the point where future benefits (in terms of climate-change damage avoided by reducing one unit of GHG emissions) are just equal to the corresponding costs (of mitigation measures required to reduce that unit of GHG emissions), i.e. MAC = MAD at point ROP. Durable strategies become more relevant when MAC and/or MAD might be poorly quantified and uncertain. Figure 5.2(b) assumes that MAC is better defined than MAD. First, MAC is determined using technoeconomic least-cost analysis (an optimizing approach), while MAD is ignored. Next, the target emissions are set, based on an affordable but safe minimum standard (at RAM). This value is the upper limit on mitigation costs that will still avoid unacceptable socioeconomic disruption. This choice is more consistent with the durability approach. Finally, Figure 5.2(c) indicates an even more uncertain world, where neither MAC nor MAD is defined. Here, the emission target is established based on an absolute standard

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(RAS). Typically, such a safe limit could seek to avoid an unacceptably high risk of damage to ecological (and/or social) systems, without necessarily valuing any costs in monetary terms. This last approach is based mainly on the durability concept.

5.4.2 Combining efficiency and equity to facilitate South–North cooperation for climate-change mitigation Figure 5.3 clarifies the basic rationale for greater North to South cooperation through resource and technical transfers, and highlights how the sustainomics approach elucidates the complex interaction of economic efficiency and social equity in addressing the climatechange problem. The vertical bars indicate the marginal abatement costs for two countries (X is a developing or southern country and Y is an industrialized or northern nation). In other words, the bars show the net additional costs per unit of GHG emissions reduced by mitigation schemes (over and above the costs of conventional technologies, and including all ancillary costs and benefits). The figure assumes that GHG-emission reduction options are cheaper in the developing country than in the industrialized nation. The global benefit of mitigation is shown by the upper horizontal line representing the MAD accruing to the entire global community due to GHG-emission reductions. The MAD realized by the developing country alone would be negligibly small, since abatement measures undertaken by any given nation will yield predominantly worldwide benefits well beyond its borders. Clearly, if the developing country acted just in its own interests, it

MAD (global)

benefit global net benefit (NB) CostY ShareY

ShareX

total cost saving (S)

CostX

country X

country Y

Figure 5.3. Interplay of efficiency and equity and rationale for North–South cooperation.


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would be unwilling to incur any incremental costs of mitigation. In such a situation, only so called ‘win–win’ or ‘no-regrets’ options would be pursued – such as energy-efficiency schemes where there is a net economic gain, even without considering GHG-abatement benefits. Global mitigation benefits would be considered an ‘externality’ by the developing country. From the strict economic efficiency perspective of the entire world community (see Box 2.3) and ignoring equity issues, mitigation options need to be pursued in all countries, up to the point where additional costs of a marginal unit of emissions curtailed are equal to the corresponding benefits of avoided global-warming damages. In this case, the avoided damages that are ‘external’ to the mitigating country should be ‘internalized’ from the global viewpoint. First, we explore how such an efficiency-based approach might support resource transfers from North to South. Consider a representative GHG mitigation project (e.g. reafforestation) in the developing country X, where the additional costs of GHG-emission reduction is less than the global avoided damage. From the perspective of the global development community (i.e. rich countries), it would be economically efficient for them collectively to finance any additional costs (e.g. on a grant basis) in the developing country. They would thereby ‘internalize’ and capture the worldwide net mitigation benefits equivalent to NB + S (see Figure 5.3). Second, we make the case for a bilateral transfer of resources from an industrialized to a developing country. Consider the cost of a project (e.g. the conversion of coal plants), which seeks to reduce GHG emissions in the industrialized country Y. This country could realize a cost saving if it pursuaded the developing country X to undertake the mitigation measure, while still achieving the same global-emissions-reduction benefit. The minimum compensation acceptable to country X would be its CostX. The maximum payment country Y would be willing to make is S (CostY – CostX). This could be the basis for cooperative schemes, such as joint implementation (JI) and the clean development mechanism (CDM). If the net benefits, NB, and cost savings, S, are adequate, it would be both equitable and efficient for the industrial nation to give the developing country more resources than the break-even reimbursement CostX. For example, the cost saving could be shared in the proportions ShareY and ShareX between the industrial and developing nations, respectively (ShareX + ShareY = S). Sustainomics would favour such an equitable sharing of potential cost savings between the two cooperating nations (see Section 5.2.3). This would also provide more incentives for developing countries to participate in such a scheme. Munasinghe and King (1992) made the same proposal in the case of South–North cooperation to reduce ozonedepleting substances under the Montreal Protocol.

5.4.3 Equity and efficiency in emissions trading Equity and efficiency principles may be applied usefully in allocating the mitigation burden among various countries to achieve a future target level of desirable worldwide GHG emissions (see Section 5.2.3). Suppose there is international agreement to aim for stabilization

158


per capita GHG emissions

Key A1 = annex I countries average NA1 = non-annex I countries average

A1

AV = current global average

PR1

PC = equal per capita rights target PR1 = equi-proportional reduction for annex I

buy

PR2 = equi-proportional reduction for non-annex I T1 = transition emissions profile for annex I AV

T3 T1 T2

PC sell

NA1

T2 = transition emissions profile for non-annex I T3 = trading emissions profile for annex I

T4

T4 = trading emissions profile for non-annex I

PR2

2000

2100

Figure 5.4. Combining equity and efficiency in emissions trading.

of GHG concentrations, say in the range 550 ppmv in the next 200 years. This would determine the total global-emissions budget in the future. Consider two contrasting rules for allocating rights to the fixed global level of future emissions, year by year among the different nations. (1) Equal per capita (PC) emission rights for all human beings, based on ethics and human rights. The total national ‘right to emit’ would be the product of the population and the basic per capita emissions quota, with all national quotas summing to the desired global-emissions target. (2) Equi-proportional reductions (PR) of emissions, based on so-called ‘grandfathering’. In this case, all countries would reduce emissions by the same percentage amount relative to some pre-agreed baseline year, to achieve the desired global-emissions target.

The dynamics of this allocation process are shown in Figure 5.4. The line PC indicates the constant level of per capita emissions if the total global-emissions target were allocated equally to all human beings during the decision-making time horizon. The points A1 and NA1 represent the average current per capita GHG emissions of the Annex I (industrialized), and non-Annex I (developing) countries, respectively; A1 is considerably larger and NA1 is somewhat less than PC. Thus, the industrialized countries would need to incur economic costs to cut back GHG emissions significantly, if they were to meet the PC criterion. On the other hand, the developing countries have some ‘headroom’ to increase their per capita emissions, as incomes and energy consumption grow. The alternative allocation rule is based on equi-proportional reductions (PR) of emissions. Assuming that the global average emission rate per capita per year is slightly higher than PC; this implies that all countries would need to curtail carbon emissions by a small amount


159

(say about 10%) to meet the PR criterion (as shown by the broken lines PR1 and PR2 in Figure 5.4). Clearly, such an outcome is highly inequitable, since it would severely restrict growth prospects in the developing world – where per capita energy use is still quite low (Munasinghe, 1995a). Thus, both developed and developing countries would have reasons to oppose strict enforcement of the PC and PR approaches. Meanwhile, the developing countries argue that responsibility for past emissions should be considered when future rights are allocated. Clearly the industrialized countries have used up a significant share of the ‘global carbon space’ available to humanity while driving up atmospheric CO2 concentrations from the preindustrial norm of 280 ppmv to the current level of over 380 ppmv. On the other hand, it would be in the industrialized countries’ interests to use a fixed-base-year population (e.g. in the year 2000) as the multiplier of the per capita emissions right (e.g. PC) to determine total national emission quotas. This would effectively penalize countries which had highpopulation-growth rates, since their allowed national quota (determined by the base-year population) would have to be divided up among more people in the future. In practice, it is possible that some intermediate requirement that falls between PC and PR might eventually emerge from the collective decision-making process. For example, PC may be set as a long-term goal. In the shorter run, pragmatic considerations suggest that both the industrialized and transition countries be given a period of time to adjust to the lower GHG-emissions level, in order to avoid undue economic disruptions and hardship – especially to poorer groups within those countries (see transition emissions paths T1 and T2 in Figure 5.4). While some industrialized nations might argue that the goal of equal per capita emissions is too idealistic or impractical, the direction of adjustment is clear. Net CO2 emissions per capita in industrialized countries should trend downwards, while such emissions in developing countries will increase with time. This result will emerge even if the objective is a more equitable distribution of per capita emissions, rather than absolute equality (the so-called ‘contraction and convergence’ scenario). Another adjustment option could be the facilitation of an emissions-trading system. For example, once national emissions quotas have been assigned, a particular developing country may find that it is unable to utilize its allocation fully in a given period. Meanwhile, an industrialized country might find it cheaper to buy such ‘excess’ emissions rights from the developing nation, rather than undertaking a much higher cost emissions-abatement programme to meet its own target (see Section 5.5.2). More generally, the emissions-trading system would permit quotas to be bought and sold freely on the international market – thus establishing an efficient current price and a futures market for GHG emissions. In Figure 5.4, new transition emission profiles T3 and T4 might emerge, creating potential space for adjustment through the buying and selling of carbon rights.

5.5 Greenhouse-gas-mitigation prospects in Sri Lanka In this section, we discuss how a global problem like climate change might interact with sustainable development prospects at the national level – through a case study that examines

160


GHG-mitigation prospects in Sri Lanka. Furthermore, in Section 5.6 we develop a basic real options analytical framework to deal with significant uncertainties facing Sri Lankan decision makers in responding to opportunities offered by the Kyoto Protocol’s flexibility instruments (i.e. CDM, JI and emissions trading). The following procedure is used in this ‘bottom-up’ case study: (a) estimate GHG emissions for the reference (business-as-usual) scenario; (b) estimate GHG emissions for a reform scenario to assess the impact of pricing and other policy interventions typically undertaken by the government; (c) identify, evaluate and screen a range of GHG-mitigation options; (d) formulate alternative mitigation scenarios and estimate the GHG impacts of each scenario; and (e) compare them to the reform scenario to gauge the cost-effectiveness of the GHG-emissions-reduction options. First, power-sector GHG emissions are estimated for a reference (or business-as-usual) scenario. The least-cost capacity expansion programme is developed to satisfy the growth of electricity demand for 20 years, while meeting acceptable levels of reliability and environmental protection standards. Next, the GHG emissions associated with a reform scenario (including various policy options) are estimated. Several mitigation options are screened and then combined within alternative GHG mitigation scenarios, which are compared to the reference and reform scenarios. The modelling was achieved with ENVIROPLAN used in the 1990s to study environmental issues in the Sri Lanka power sector (Meier and Munasinghe, 1994), and subsequently applied in many other countries (BC Hydro, 1995; USAID, 1995; World Bank, 2004).

5.5.1 Baseline emissions Biomass still accounts for the largest share of primary energy (see Table 5.1), although the share of commercial energy has grown steadily since 1984. The corresponding changes in GHG emissions are shown in Table 5.2 (Ratnasiri, 1998). However, the increases in powersector emissions from 1990 to 1992 are due solely to the variation of hydro generation (1991 and 1992 were dry years), rather than any change in generation capacity. Table 5.1 Shares of total primary energy 1984

Biomass Commercial Total

1996

1000 TOE

%

1000 TOE

%

1984–1996 change (%/year)

4203 1700 5903

71 29 100

3925 2952 6877

57 43 100

− 0.6 4.71 1.28

TOE = tonnes of oil equivalent; ‘Commercial’ includes hydro and oil; 1996 was a drought year, in which the share of hydro was lower than normal. Source: Energy Conservation Fund (1996).


161

Table 5.2 Estimates of CO2 emissions by source, 1990–1992 (thousand tonnes)

Power (CEB) Transport Energy generation in industry Commercial (fisheries, agriculture) Domestic (LPG, kerosene) Cement/lime production Refinery own use Total energy and industrial processes Biomass Emissions from agriculture, land-use and waste

1990

1991

1992

8.5 2214 559 172 550 249 0.7 3899 21 261 8435

226.6 2317 485 161 578 244 0.6 4120 20 095 8370

643.2 2334 561 166 651 436 0.7 4894 21 498 8098

CEB = Ceylon Electricity Board. Source: Ratnasiri (1998).

This situation is changing since the share of hydroelectricity in Sri Lanka’s energy mix continues to decline, and almost all new power plants over the next two to three decades will be fossil-fuelled. Wind power, mini-hydro and demand side management will also increase in importance in the near future. Consequently, in the business-as-usual case, the share of GHG emissions from the power sector will increase from 18% of energy-sector emissions in 1998 to 45% in 2018; in absolute terms, the power sector will account for 20.1 million tonnes per year (mtpy) by 2018, compared with 1.7 mtpy in 1997, a more than tenfold increase. Emission coefficients and conversions GHG-emission coefficients are calculated by stochiometry, and where these data are unavailable, IPCC emission coefficients are used. To convert non-carbon dioxide GHGs to carbon equivalents, the IPCC 100-year equivalent global-warming potentials are applied (IPCC, 2001a, 2007a).

5.5.2 Base case or business-as-usual scenario The ‘base case’ in the Ceylon Electricity Board (CEB) annual long-term generation expansion planning study is used here as the business-as-usual case (CEB 1988, 1999). GDP growth is the dominant determinant of demand (CEB, 1988). In the businessas-usual demand forecast, the tariff is assumed to rise with inflation (constant in real terms). By 2018, the busbar peak demand is estimated to grow to 4292 MW (compared with 1136 MW in 1998); the corresponding 2018 energy demand is 20 678 GWh, up from 5683 GWh in 1998. Total T&D loss rates, and the system load factor (SLF), are

162


Table 5.3 Generation capacity expansion for wind power case All values are in megawatts; negative values indicate retirement 1999 Hydro Coal Liquid fuels Gas Diesel

2001 2003

2005

70

100

300

2009

2011 2013

2015

2017

150 300

106

2007

300

300 105 105 −36

300 105 105 105

300 300

300

−13

taken as 17.6% (of generation) and 55%, respectively, which are their 10-year average values (both have stayed remarkably constant over the past decade). Of the total T&D loss, 15.3% is technical loss, and the balance of 2.3% is non-technical (commercial) loss. Table 5.3 shows the resulting capacity expansion plan for the business-as-usual (BAU) case.

5.5.3 Reform scenario In Sri Lanka, the specific components of a comprehensive reform initiative are still evolving. Nevertheless, the following elements might be part of a power-sector reform programme: (a) greater T&D loss reduction (e.g. due to distribution privatization); (b) implementation of the remaining cost-effective DSM options; (c) improvements to timeof-day tariff; and (d) tariff reforms (higher average price). T&D losses are assumed to fall steadily from 17.8% of generation (15.5% technical and 2.3% non-technical) in 1999, to 12.5% (11% technical and 1.5% non-technical) in 2007, and then to remain constant. It is assumed that, in the first stage of reform, DSM-1 would be limited to lighting. Energy-efficient motors and AC systems are considered later under DSM-2. By 2007, lighting DSM-1 reduces the peak evening demand by 330 MW, about 15% of the total evening peak load. As shown in Table 5.4, the combination of reduced T&D losses and the peak-shaving impact of the lighting DSM-1 programme reduces the generation requirement compared with the base case. Baseload coal units decline from six to five, and thermal peaking units decline from six to two 105 MW open cycle combustion turbines (OCCTs) from 2010 to 2018. There is a corresponding 15% reduction in GHG emissions, from 118 million tonnes over the planning horizon in the base case to 98 million tonnes under reform (Figure 5.5). This is a win–win outcome. By contrast, in the Indian state of Haryana, the economic benefits of reform are six times larger than in Sri Lanka, but this results in a 25% increase in GHG emissions – due to major inefficiencies such as T&D losses of 35% (World Bank, 1997b). The impact of reforms on system costs and GHG emissions can be displayed as a trade-off plot in Figure 5.6. The impacts of T&D loss reduction and DSM-1 are shown separately


163

Table 5.4 Generation capacity expansion for reform case All values are in megawatts; negative values indicate retirement 1999 Hydro Coal Liquid fuels Gas Diesel Renewables

2001 2003

2005

70 106

2007 150 300

2009 300

2011 2013 2015 300

300

300 −36

100

−36

15

GHG emissions (106 tonnes)

BAU

10

reform

5

0 change relative to: BAU[#] –5

1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018

Figure 5.5. GHG-emission reductions. 2800 BAU

PV (system cost)

2700 T&D loss reduction 2600 DSM-1 2500 reform 2400 95

100 105 110 115 120 total GHG emissions, undiscounted (million tonnes)

Figure 5.6. Impact of reform on system costs and GHG emissions.

125

2017 300 105 105

164


(each as perturbations of the BAU case). Reform is clearly ‘win–win’; indeed, reform is also win–win with respect to other environmental attributes for local air emissions.

5.5.4 Mitigation options We next analyse individual mitigation options separately, as an increment to the reference (reform) case. The goal is to compare the cost of avoided carbon for individual options and construct GHG-mitigation scenarios. Individual options are combined to generate a GHGmitigation option supply curve that includes interactions among individual programmes. The focus is on the economic costs and magnitude of the physical GHG-emission-reduction benefits – expressed as the price of avoided carbon. Many alternative-energy options have upward-sloping supply curves; this is attributable to two main reasons. The first applies to situations where capital costs are likely to be relatively constant across individual projects, but where energy output between the best and worst sites shows large differences (e.g. wind power). The second applies to the converse case – where plant factors might show relatively small differences, whereas construction costs may show high variation (e.g. small hydro). Alternative-energy options Small hydro Grid-connected small hydro is the largest single component of the IDA/Global Environment Facility Energy Services Delivery Project (ESDP), comprising US$ 14.4 million of US$ 24.2 million (World Bank, 1997a). Four such small hydro plants, totalling about 1.3 MW, were connected to the CEB grid in 1996 and 1997. Based on studies by Posch and Partners (1994) and Fernando (1998), we divide the minihydro potential into two tranches: a first tranche of 10 MW of the larger projects with capital costs of less than US $1100/kW, implemented in 2000–2002 (mini-hydro I) and a second tranche of 35 MW of smaller projects costing US $1100–US $1500/kW, implemented between 2001 and 2007 (mini-hydro II). One of the main constraints to small-hydro development is the adequacy of the tariff. Presently, the CEB tariff is based solely on avoided energy costs, with no capacity credit – which is disputed by developers. The main CEB argument against a capacity benefit is that results from their WASP model show little or no impact of small hydro on the optimal capacity expansion plan. On the other hand, even in the driest months, there is still some mini-hydro generation. As more mini-hydro plants are built, the diversity effect is likely to increase the capacity value to CEB. In other words, while the capacity benefit of any single plant may be small because of the water flow variation of a particular site, the aggregate outputs of all small-hydro-projects provide more firm capacity. In some locations, while individual technologies cannot be diversified, combinations of different renewable technologies may provide diversification and increase the capacity credit for the renewables portfolio as a whole. For example, just such a combination may


165

Table 5.5 Generation capacity expansion for wind-power case All values are in megawatts; negative values indicate retirement 1999 Hydro Coal Liquid fuels Gas Diesel Renewables 3

2001

2003 70

2005

2007

2009

2013

2015

2017

150 300

106

2011

300

300 300 105 105 105 105 105 105

100 −36 −36 30 30 30 60 60 75 75 75 75 150 150 150 150 150 150 150 150 150 150

be possible in the Eastern China province of Zhejiang, where small hydro peaks in summer and wind peaks in winter. Wind power Sri Lanka’s wind climate is characterized by two monsoon systems – the stronger southwest monsoon, lasting from May to early October, and the northeast monsoon, from December to late February. With strong to moderate winds prevailing for about eight months of the year, Sri Lanka has a modest potential for wind-power generation. A 3 MW wind-power demonstration is underway with the support of the Extending Service Delivery (ESD) project, with an estimated capital cost of US $1175/kW. Sri Lanka lacks good quality historical wind data to make a reliable assessment of windenergy potential. Nevertheless, some tentative conclusions regarding windy regions in Sri Lanka could be drawn from existing wind data and also natural indicators. About 3600 MW of potential generation have been identified, mainly in the southern and southeastern lowland regions (CEB, 1992). The WASP model was used to examine the maximum amount of wind power that could be absorbed by the system while meeting the CEB planning criteria (loss-of-load probability, LOLP, of less than 0.1%). These studies reveal that up to 2000 MW could be absorbed into the system over the planning horizon. The CEB capacity expansion plan for the maximum-wind-power scenario is shown in Table 5.5. Uncertainties in both costs and wind data underline the need for caution and better data. We assume a decrease in capital costs from the present US $1175/kW to US $1000/kW over the planning horizon. Far lower capital costs may be achieved if the rate of progress in wind-turbine technology achieved over the past decade continues into the future. On the other hand, a Danish study of 1080 wind-power sites over a period of six years showed that the actual annual production is 12% lower than predicted at the time of wind-farm design. Reasons for this discrepancy may be overoptimistic estimates of future turbine costs, lower reliability of machines and overestimates of wind availability. Dendro-thermal power The main rationale for dendro-thermal generation is its potential to displace costly fossilfuel imports, while generating employment (Wijewardene and Joseph, 1999). Such power

166


Table 5.6 Generation capacity expansion for dendro-thermal case All values are in megawatts; negative values indicate retirement 1999 Hydro Coal Liquid fuels Gas Diesel Renewables

2001 2003

2005

70 106 100

2007

2009

2011

2013

2015

2017

105

105 105

150

300 −36 10 100 0

−36 100 100 150

150

200 200

200 0 200 0

Table 5.7 Assumptions for dendro-thermal power plants

Unit size (MW) Capital cost (US$/kW) Fixed O&M (US$/kW/month) Variable O&M (non-fuel) (US$/MWh) Heat rate (Kcal/kWh) Sulphur content (%) Heat value as received(a) (Kcal/kg) Fuel cost (at plant gate) (US $/tonne) Land area for fuelwood plantation (Ha/MW)

Dendro (gasifier)

Coal plant

10 1200 1.8 2.5 4560 0.02 3800 22 360

2 × 300 899 0.64 3.54 2162 0.6 6300 48

(a)

Assuming 20% moisture for fuelwood. Source: Based on information provided by P. G. Joseph of the Sri Lanka Energy Conservation Fund.

plants require substantial land for the necessary fuelwood plantations – in Sri Lanka, advocates argue that 1000 MW of dendro-thermal would use only 360 000 hectares of scrub and chena lands (20% of total available). Increments of dendro-thermal (50 MW) power for GHG mitigation were tested as an alternative to baseload coal plants. This results in the capacity expansion plan indicated in Table 5.6 – fuelwood costed at US $22/tonne. Cost assumptions for dendro- versus coal-fired power are summarized in Table 5.7. It is assumed that gasifier rather than combustion (steam-cycle) technology is employed. The fuel cost of US $22/tonne is based on the present price of fuelwood delivered in Colombo. Fuelwood produced in properly managed plantations near the power plants may reduce this cost. Therefore, an alternative dendro-thermal fuel-cost price of US $14/tonne was also analysed. Solar photovoltaic systems Solar photovoltaic (PV) systems for remote rural homes (‘solar homes’) represent another component of the ESD project with Global Environment Faculty (GEF) support to


167

overcome institutional and financing constraints – the ESD programme provides a US $100 grant per solar home module of 30 W or greater. In the solar homes scenario, we assume that, by 2018, about 85% of the then remaining unelectrified homes would be served by solar systems, representing about 500 000 systems in place. This is significantly greater than the present estimate of between 100 000 to 215 000 homes considered by private vendors as the present potential market, taking into account affordability criteria (Jayewardene and Perera, 1991). Given the GDP growth assumed for the power demand forecast, a doubling of real income is possible over the 20-year planning period. We also assume that the present cost of US $6000/kW will decrease over time, reaching US $1000/kW by 2018, and the unit output per system would increase from the present 30–50 W to 200 W by 2018. These mildly optimistic assumptions seem warranted in order to determine the bounds of potential cost-effectiveness for GHG mitigation. Fuel substitution options Oil steam-cycle plants For this GHG assessment we assume that 3.5% high-sulphur fuel oil would be imported from the Gulf, and that flue gas desulphurization (FGD) would be required. The plant characteristics are taken from Electrowatt (1996). Liquid nitrogen gas (LNG) The LNG price delivered to the plant gate is taken as US $5/MMBtu. This includes the cost recovery of the up-front infrastructure costs (terminal, gas storage, regasification facility, etc.) Capital and operating costs of the power-generation plant, heat rate, etc., may be taken as the same as for diesel-fuelled combined-cycle plants. Conventional hydro In addition to the Kukule and Upper Kotmale projects already in the least-cost generation expansion plan, additional plants (see Table 5.8) were forced into the plan to produce a maximum hydro development scenario (MaxHy) for GHG mitigation.

Table 5.8 Additional hydro-projects for the maximum hydro scenario

Broadlands Gin Ganga Moragolla Uma Oya (a)

Start-up year

MW

Capital cost ($/MW)(a)

2005 2005 2007 2010

40 49 27 150

2548 2127 3002 2152

Pure (overnight) project cost, without interest during construction, customs or duties.

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Biomass co-firing Biomass co-firing at the proposed coal-fired plants was considered. Supplying 15% of the energy input from fuelwood should be feasible at minimal modification of the coal plant (about US $75/kW) – based on the EPRI Technical Assessment Guide. DSM In addition to the lighting DSM-1 in the reform case, further GHG mitigation may be achieved by DSM-2 through energy-efficient motors (EEMs) and DSM-3 with energyefficient air conditioning (EEAC).

5.5.5 Results The screening analysis is summarized in Table 5.9. Note that the reductions in emissions in columns [4] and [5] cannot be added, since the individual data points represent perturbations of the reform scenario, one at a time (and some are mutually exclusive, such as LNG, oil steam-cycle with FGD, or the dendro-thermal options at different delivered wood costs). Negative costs of avoided carbon indicate ‘win–win’ options. Figure 5.7 shows these data differently, plotting system cost against GHG emissions (undiscounted CO2), with the four quadrants defined by the reform case. The slope of the line connecting any point with the reform case defines the cost of avoided carbon (see column [6] of Table 5.9). These results are unsurprising. The most expensive option is the solar homes programme at US $184/tonne of carbon. However, this result is a good example of the hazards of conducting the analysis in terms of changes in system costs rather than changes in net benefits. When benefits of providing lighting and TV in off-grid areas are properly assessed, the solar home option brings significant net benefits (see Section 15.7.1).

Impact on local air emissions Implementation of GHG emission reduction measures also reduces local air emissions (SO2, NOx, particulates). However, the monetized value of these local environmental benefits is small in comparison to the cost of avoided carbon. GHG emission reduction scenarios Starting with BAU, individual mitigation measures are brought into the solution cumulatively. The criterion for introducing the next measure could be the next lowest cost of avoided carbon, or the measure most likely to be implemented. For example, starting with BAU, the first step could be either DSM (which has the best cost of avoided carbon) or T&D rehabilitation. In Figure 5.8, T&D loss reduction is the first step. Table 5.10 shows the order in which the measures are brought into solution, reaching the least-cost scenario (step [8]) after introduction of all of the DSM, mini-hydro and further


169

Table 5.9 Cost of avoided carbon

Reform +DSM-2: EEM Oil–steam (resid.) Oil–steam (resid.) + FGD +DSM-3: EEAC Oil–steam + FGD +T&D (to 10%) Mini-hydro: I Mini-hydro: II Dendro-thermal ($14/tonne) Oil–steam (0.3%S) Dendro-thermal ($22/tonne) Diesel ($800/kW) LNG Diesel ($1140/kW) MaxHy Wind (max.) Solar homes

Cost CO2 System difference emissions cost (relative (million (million $) to reform) tonnes)

CO2 difference (relative to Carbon Cost of avoided reform) difference carbon ($/tonne C)

[1]

[2]

[3]

[4]

2449 2430 2325 2362

−18.5 −123.7 −87.2

98.4 96.6 83.1 83.1

−1.8 −15.3 −15.3

−0.5 −4.2 −4.2

−37.6 −29.7 −20.9

2441 2416 2440 2448 2450 2492

−7.6 −33.2 −9.2 −0.8 1.5 42.7

96.4 88.5 95.2 97.5 95.7 39.2

−2.0 −9.9 −3.2 −1.0 −2.7 −59.3

−0.6 −2.7 −0.9 −0.3 −0.7 −16.2

−13.6 −12.3 −10.4 −3.2 2.1 2.6

2465 2580

16.5 131.1

88.6 39.6

−9.8 −58.8

−2.7 −16

6.1 8.2

2494 2545 2580 2553 2870 2490

45.3 96.3 130.9 104.0 421.2 41.6

83.8 77.3 83.8 88.3 74.8 97.6

−14.6 −21.1 −14.6 −10.1 −23.7 −0.8

−4 −5.8 −4 −2.8 −6.5 −0.2

11.4 16.7 32.8 37.7 65.3 184.5

[5]

[6]

T&D loss reduction. Any further measures to reduce GHG emissions would then begin to increase costs. By the time we reach the economic least-cost scenario (all the DSM, mini-hydro and further reduction of T&D losses), which is the lowest point on the curve, the number of coal plants over the planning horizon has reduced further from the five in the reform scenario to four.

5.5.6 Developing the standard abatement cost curve (SACC) Table 5.11 shows the avoided costs of carbon and the percentage reductions (relative to the BAU case) achievable in each scenario. Win–win options, when considered as a stand-alone perturbation of the reform case, may not remain win–win when combined with other win– win options. In Table 5.11, introducing oil–steam + FGD after the last tranche of mini-hydro increases costs, and is therefore no longer win–win.

170

Global and transnational applications 3000

wind (max)

PV (system cost)

2800

BAU

T&D loss reduction diesel ($1140/kW)

2600

dendro-thermal ($22 /tonne) MaxHy LNG diesel ($800 /kW) dendro-thermal ($14/tonne)

solar homes

oil steam (0.3%S)

reform

oil steam+FGD

2400

oil steam (residual) +FGD oil steam (residual)

2200 20

40

60 80 100 total GHG emissions, undiscounted (million tonnes)

120

140

Figure 5.7. System cost versus GHG emissions.

2800 [1]BAU

PV (system cost)

2700 [2]T&D loss reduction

++ wind

2600 DSM

++ MaxHy

2500

[10] + dendro

++ LNG ++ diesel

[3]reform [4]+DSM:indEEM

[9]

2400

[7] [6] [8]

2300 50

70

90

110

130

GHG, undiscounted (million tonnes)

Figure 5.8. Defining the GHG-mitigation scenario.

The corresponding GHG-mitigation supply curve – where we introduce each measure in order of avoided cost – is shown in Figure 5.9. Here we draw the SACC in tonnes of carbon (rather than tonnes of CO2). In such a standard deterministic framework, all the steps that lie below the emission-trading price should be pursued if decision makers seek to maximize the

Measure

C>

X X X X X X X X X X X X X X X

Cost of avoided carbon, $/tonne

Scenarios 1 BAU 2 +T&D > 12.5% 3 Reform 4 DSM:indEEM 5 +DSM:commAC 6 +MiniHy I 7 +T&D > 10% 8 +MiniHy II 9 Oil–steam (+FGD) 10 Dendro-thermal 11 Diesel 12 LNG 13 +MaxHy 14 +Wind 15 +Solar homes

X X X X X X

−82

X X X X X X X X X X X X X

−35

X X X X X X X X X X X X

−50

X X X X X X X X X X X

−20

X X X X X X X X X X

−16

X X X X X X X X X

−14

X X X X X X X X

−0.5

X

−21

CBB T&D DSM DSM DSM T&D Oil–steam base case >12.5% lighting ind EEM comm AC MiniHyI >10% MiniHyII + FGD

Table 5.10 Definition of mitigation scenarios

X X X

X

8

X

11

Dendro Diesel

X

16

X X X

38

X X

66

X

150

Solar LNG MaxHy Wind homes

Mutually exclusive options

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Table 5.11 GHG-mitigation scenarios

Scenario

Cost System cost difference CO2

BAU T&D loss reduction Reform DSM:indEEM DSM:commAC Mini-hydro I T&D > 10% Mini-hydro II = least-cost Oil–steam ++FGD Dendro Diesel LNG MaxHy Wind

2775 2653 2449 2430 2425 2423 2403 2393 2402 2481 2500 2465 2540 2639

382 260 56 38 32 30 10

118.0 107.1 98.4 96.6 95.3 94.6 90.5 87.8 79.6 46.2 75.4 70.2 49.8 50.1

10 89 107 73 147 246

CO2 $/tonne % reduction difference C (BAU) 19 11 9 7 7 3

−49.5 −19.4 −15.7 −15.7 −16.2 −13.8

−8 −42 −12 −18 −38 −38

4.4 7.8 31.6 15.2 14.2 23.9

9 17 18 19 20 23 26 33 61 36 41 58 58

20

cost of avoided carbon ($/tonne C)

[10] dendro [9] oil–steam+FGD

0

[8] least cost = MiniHyII

[4]

[5]

[6]

[7] T&D >10%

–20 [3] reform

–40 [2] T&D loss reduction

–60

0

20 40 60 emissions reduction (million tonnes of carbon)

Figure 5.9. Standard abatement cost curve for Sri Lanka.

80


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net benefits of abatement. However, uncertainty introduces complications that require a more dynamic framework, as shown below.

5.6 Real-options framework for carbon trading under uncertainty The results of the previous section help to identify an appropriate GHG strategy for Sri Lanka. However, there are large uncertainties, including the value of carbon in international trading – which could range from zero, if a market for carbon reductions does not develop, to values in excess of US $20/tonne if evidence of global warming begins to appear.

5.6.1 Sources of uncertainty and the real-options approach Uncertainty calls for the options-based approach to be used to enhance the traditional net present value (NPV) rule used in CBA. Jepma and Munasinghe (1998) classify uncertainty related to climate change into two broad categories. First, scientific uncertainty arises due to limited knowledge of rates of natural emission and absorption, and of environmental consequences of GHGs. Second, socioeconomic and technological uncertainty linked to human actions arises from the difficulty of predicting the future rates of emissions, the inability to value in monetary terms the future impact of climate change and other forms of environmental degradation, lack of knowledge about human responses to environmental changes and lack of knowledge about the development of technological options, which would affect all aspects of the environmental equation. Climate change has a long time frame, with forecast periods of over 100 years. Even small uncertainties can lead to a wide range of outcomes over such long time periods (Munasinghe and Swart, 2005). Standard and dynamic abatement cost curves In this section, we follow the model developed in Fernando and Munasinghe (1998). An important first step in the bottom-up approach to mitigation is the identification of the options available for reducing emissions. A standard abatement cost curve (SACC) for GHG mitigation options (as in Figure 5.9) is obtained by deterministically ranking specific GHG mitigation projects in the order of cost (or benefit in the case of ‘win–win’ projects) of reducing a unit of carbon emissions. The costs and benefits of GHG mitigation are obtained by discounting future streams of value back to the present time. Projects with a lower cost per unit of carbon reduction should be implemented prior to higher-cost projects. This static approach can yield misleading results, especially in the case of GHG mitigation projects, which can vary widely with regard to time frame, the cost of reversal and the uncertainty associated with future costs and benefits. This is because the SACC, which is based on the assessment of future costs and benefits at a particular instant in time, disregards the value of the options embedded in specific projects associated with changing the timing of their implementation. Taking such options into account may lead to a reversal in the ordering of projects along the SACC or control-cost staircase.

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For example, higher-cost (but lower-option-valued) projects might be undertaken prior to their lower cost (but higher-option-valued) counterparts. This option value will arise, in part, from the fact that the control-cost curve is itself dynamic, with changes brought about due to the evolution of science and technology, as well as socioeconomic conditions. Developing a dynamic abatement cost curve (DACC) would require taking account of each of the above drivers of option value, for each of the GHG mitigation options that have been identified in the SACC. To show how risk and uncertainty might affect the SACC, consider a deterministic case where the cheapest mitigation option (step A) would be to increase energy prices, while the next best option (step B) is energy conservation. In a riskless analysis, the decision maker would first carry out step A, then go to step B. However, in reality, public reaction against energy-price increases may involve a greater political risk – it may be preferable to undertake step B first and defer step A until later. Thus, political uncertainty and risk could change the decision-making process. Uncertainties in future technology costs or carbon offset values could also result in the transposition of steps, compared to the deterministic case. This decision problem can be analysed using a real-options framework, which has been used extensively in other fields. Box 5.3 illustrates the basic concept using a simple numerical example. Fernando and Munasinghe (1998) provide a detailed description.

5.6.2 Applying the real-options approach Oil–steam (+FGD) In Table 5.12, we examine the use of oil–steam (+FGD) as a mitigation measure, starting from the least-cost scenario. As shown in panel A, this increases the system cost by US $9.7 million and decreases GHG emissions by 8.1 million tonnes, with a discounted cost of avoided carbon of US $21.2/tonne (which falls to US $4.4/tonne when undiscounted). Panel B shows the probability distribution for the value of the carbon offset, expressed as US $/tonne C. The expected value of the carbon offset, E{V(C)}, is US $22. The corresponding expected value of carbon offset revenue, E{R(C)}, is US $10.1 million when discounted at 10%; E{R(C)} is given by EfRðCÞgd ¼ SVjPfjgDC; where ΔC is the avoided carbon (8.1 million tonnes in this case) and P{j} is the probability of the carbon offset having value Vj. Panel C of Table 5.12 then derives the expected value of implementing this mitigation option today, which is the cost given in Table 5.12, panel A (NPV of US $2402.3 million), less the expected value of revenue from carbon offsets (US $10.1 million). This is US $0.4 million less than the least-cost case (US $2392.6 million). This reduction in cost (though only about 4% of the expected value of the carbon offset revenue) would normally justify undertaking the mitigation measure (given the expected value of US $22/tonne for carbon offsets).


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Box 5.3 Calculation of option values Consider an environmental project that requires an investment of US $100 million. Based on the information available today (time 0), this project will yield an environmental credit valued at US $200 million (good state) or US $50 million (bad state), with equal probability, a year from now (time 1). The project terminates at time 1. With a discount rate of 10%, the NPV is given by NPV ¼ 0:5 f200=1:1g

þ

return in year 1 Prfgood stateg

0:5f50=1:1g

100

return in year 1 Prfbad stateg

¼ US $13:6 million

cost of investment

The standard NPV rule would recommend that this project be undertaken in order to realize the expected positive net present value of US $13.6 million. Suppose the project can be postponed at a cost of US $5 million, and that one year from now it will be known whether the state is good or bad. If the good state is observed, the investment will be made, with a return of US $200 million at time 2. If the bad state is observed, the investment will not be made. Therefore the NPV of postponing the investment decision until time 1 is given by NPV ¼ 0:5 f200=1:12g þ 0:5f100=1:1g þ 0:5 zero 5 ¼ US $32:2 million return in year 2 cost of Prfbad stateg cost of Prfbad stateg investment ½no investment delay

Thus, although the NPV is positive, it will be suboptimal to invest in this project at time 0, since investors can gain by waiting until time 1, when the uncertainty is resolved and the expected value increases to US $32 million. Thus, the option value of delaying a decision by one year is 32.2 − 13.6 = US $18.6 million.

Panel D shows the implications of delaying a decision by five years. This delay is not costless, for instead of building the coal baseload plant now, one must build other interim capacity, such as diesels, to meet the demand. The capacity expansion plan is recalculated with the first coal unit delayed by five years and 300 MW of diesels (at US $1100/kW) built over the five-year period. Then, five years from now, one would reconsider whether to build a coal plant or to implement the mitigation measure. The new costs and GHG emissions are noted in Panel D. Because the interim diesels have some impact on the merit order dispatch, GHG emissions are different from those shown in Panel A, with a slightly higher cost of avoided carbon (US $21.9/tonne, row [7] of panel D). In panel E we show the impacts of delay. The costs increase in both cases by a roughly similar amount. The least-cost case requires a first coal plant in 2006. It follows that if the coal plant were delayed and some other interim plant were built, costs will rise by US $41.6 million. However, GHG emissions decrease by 3.1 million tonnes, since emissions from a

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Table 5.12 Oil–steam (+FGD) compared to least-cost solution All costs are in US $ A Cost and avoided carbon if implemented today

[1]

System cost (US $ million)

Undiscounted [2] GHG (CO2) (million tonnes) [3] Cost of avoided CO2 ($/tonne CO2) [4] Cost of avoided carbon ($/tonne C) Discounted [5] GHG (CO2) (million tonnes) [6] Cost of avoided CO2 ($/tonne CO2) [7] Cost of avoided carbon ($/tonne C)

Baseline: least cost

Mitigation measure ++oil–steam+FGD

2392.6

2402.3

9.7

87.8

79.6

−8.1 1.2 4.4

25.4

23.8

−1.7 5.8 21.2

Δ cost

B Expected value of revenue from carbon offsets

[1] [2] [3] [4] [5] [6]

$/tonne

Pr{j}

R(C) ($ million)

E{R(C)} ($ million)

0 10 20 30 40 Discounted value

0.025 0.150 0.500 0.250 0.075

0.00 4.58 9.15 13.73 18.31

0.0 0.7 4.6 3.4 1.4 10.1

C Expected value of implemeting measure today ($ million) [1] [2] [3] [4] [5] [6]

Cost with mitigation measure (from A, [1]) Less expected value of carbon offsets (from B, [8]) Expected cost of mitigation measure = [1] + [2] Cost without mitigation measure (from A, [1]) Cost reduction

++oil–steam+FGD

least cost

2402.3 −10.1 2392.3 2392.3 0.4 benefit: proceed

D Cost and avoided carbon if measure ++oil–steam+FGD is implemented in year 5 Interim measure Baseline: reform + 5 Mitigation measure diesel ++dendro [1] System cost (US $million) Undiscounted [2] GHG (CO2) (million tonnes) [3] Cost of avoided CO2 ($/tonne CO2) [4] Cost of avoided carbon ($/tonne C)

Δ cost

2434

2441

7.1

84.7

78.5

−6.3 1.1 4.1


177

Table 5.12 (cont.) Interim measure Baseline: reform + 5 Mitigation measure diesel ++dendro Discounted [5] GHG (CO2) (106 tonnes) [6] Cost of avoided CO2 ($/tonne CO2) [7] Cost of avoided carbon ($/tonne C)

24.6

Δ cost −1.2 6.0 21.9

23.5

E Impact of delay Baseline: reform +5 Mitigation measure ++dendro [1] System cost (US $million) 41.6 [2] GHG (CO2), undiscounted (million tonnes) −3.1

39.0 −1.2

F Decision if uncertainty resolved: calculation of option value $/tonne Pr{j} [1] 0 [2] 10 [3] 20 [4] 30 [5] 40

PV[E{R(C)}] ++Dendro

0.025 0 0.150 3.2 0.500 6.5 0.250 9.7 0.075 12.9

2441 2438 2435 2432 2428

Reform+5 Δ cost Decision

Benefit E{benefit}

2434 2434 2434 2434 2434

0 0 0 2.6 5.8

7 4 1 –3 –6

do not build do not build do not build build build

0 0 0 0.7 0.4

[6] Total expected value of carbon offsets [7] Benefit if implemented today (from C, [5])

1.1 0.4

[8] Option value of delay ([6]–[7])

0.7

diesel plant are lower than from the corresponding coal plant. Similarly, because diesels are more efficient than steam-cycle plants, replacing the first oil plant by diesels also reduces GHG emissions relative to no delay, and so GHG emissions decrease by 1.2 million tonnes per year. In panel F we now recalculate the expected values, given resolution of the uncertainty at t + 5. If the actual value of the offset is less than the cost of avoided carbon (US $21.9/tonne), then the mitigation measure is not undertaken. The converse holds with the discrete probability distribution assumed here and actual offset values of US $30/tonne and US $40/tonne. The expected value of benefits is calculated at US $1.09 million, which is greater than the US $0.37 million calculated if the decision is made today. Thus, the option value is US $1.09 − 0.37 = US $0.72 million. Although the numbers are small, the option value of

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delay is almost twice the expected value of the benefit of making the commitment to the mitigation measure today – representing about 7% of expected carbon offset revenues. Equally important is the illustration of the importance of proper discounting. Since undiscounted carbon emissions over some given planning horizon will always be greater than the corresponding discounted sum, it necessarily follows that the apparent cost of avoided carbon will be lower than if discounted. However, the economic flows that result from carbon offset payments must be discounted for valid analysis, which effectively increases the cost of avoided carbon (from US $4.4/tonne to US $21.2/tonne in this example). End effects are included by deducting salvage values from system costs. Liquid nitrogen gas A similar analysis for LNG (measured against the reform option) shows that a commitment to LNG today has an expected value of −US $69.5 million. Here, the costs of carbon offsets (US $22/tonne) are insufficient to compensate for the higher estimated cost of avoided carbon (US $79.2/tonne). Waiting for five years does not change the attractiveness of LNG, and there is no option value. In this case, the avoided cost of carbon is US $66/tonne, and even if the uncertainty is resolved and the actual value of the carbon offset rises to US $40/ tonne, the LNG option would remain unattractive. Dendro-thermal When the option value is applied to dendro-thermal power, the expected value of a commitment today is a benefit of US $31.4 million, because the cost of avoided carbon (US $10.9/ tonne) is less than the expected value of the carbon offset (US $22/tonne). However, the impact of delay is quite different for dendro-thermal than for the previous two cases. As before, forcing diesels into the least-cost solution for the interim period reduces GHG emissions. But, in the case of the dendro-thermal option, diesels will significantly increase GHG emissions – by 9.1 million tonnes. This results in an aggregate cost of avoided carbon that jumps to US $42.6/tonne. Hence, given the maximum value of US $40/tonne in the discrete probability distribution assumed for carbon offset revenue, dendro-thermal would not be implemented at t + 5. Clearly, there is no option value in this case. This counter-intuitive result arises because the economic life of diesels extends well beyond the five-year interim period. Thus, new dendro-thermal plants at t + 5 must compete against only the low variable cost of diesel plant operation, since capital costs are sunk and are no longer relevant at t + 5. However, one of the advantages of dendro-thermal is that it can be built in small increments of 1–5 MW, unlike coal plant, where the capacity increment would be 600–900 MW to capture economies of scale. Therefore, instead of the intermediate five-year commitment to diesels before choosing coal or dendro-thermal, we make a fiveyear commitment to a dendro-thermal demonstration programme, and then decide whether to go to coal or continue with a full-scale dendro-thermal programme. The corresponding option value calculation shows that the expected value for a present permanent commitment to dendro-thermal is unchanged at US $31.4 million. However, if


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the interim dendro-thermal demonstration is undertaken, the delay creates a win–win situation – the mitigation measure costs US $2482 million, which is lower than the leastcost solution (with the interim dendro-thermal demonstration) of US $2515 million, but still higher than the least-cost solution alone of US $2448 million. Nevertheless, the calculated option value is US $59.4 million, indicating the significant benefit of being able to abandon the dendro-thermal option at t + 5, regardless of the value of the carbon offset.

6 International process applications: multilevel, multistakeholder, transdisciplinary dialogues1

The case studies in this chapter focus on participatory-consultative processes relating to the social dimension of sustainable development. They describe a variety of global multilevel, multistakeholder, transdisciplinary dialogues that are crucial for making development more sustainable (see Sections 1.2.4 and 2.1.3). Within the conventional categories of government, business and civil society, epistemic communities of experts and practitioners could play a key catalytic role in cross-linking and stimulating pluralistic participation (Munasinghe, 2001b, 2004c; Sneddon, Howarth and Norgaard, 2006). The involvement of young people is also important (Focus the Nation, 2007). Section 6.1 describes how climate change and sustainable development (see Chapter 5) are handled in the Intergovernmental Panel on Climate Change (IPCC) writing process. The case study examines how this unique international dialogue among thousands of scientists is transcending barriers of discipline, space, time, stakeholder viewpoints and operationality, in addressing complex, interlinked, large-scale, long-run issues. In the second case study, Sections 6.2 and 6.3 explore two-way linkages between two other complex global initiatives – the millennium development goals (MDGs) and millennium ecosystem assessment (MA) findings. The Action Impact Matrix (AIM), a key sustainomics tool, is used to explore linkages between the two at both national and global levels. Finally, in Sections 6.4 to 6.6, we examine how a uniquely successful multistakeholder, multilevel process has been organized by the UNEP Dams and Development Programme (DDP), as a follow-up to the World Commission on Dams (WCD). It deals with key water resource issues at the international, regional and national levels (see Chapter 12).

6.1 Global transdisciplinary scientific dialogue on climate change and sustainable development The following example describes how the IPCC is addressing the complicated issues linking climate change and sustainable development, through a unique transdisciplinary international dialogue among several thousand scientists. They have developed effective modes of consultation and collaboration to assess the latest research and identify policy-relevant issues and 1

Some parts of the chapter are based on material adapted from Munasinghe (1998a, 2001b, 2002c, 2004c, 2007a).

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6 International process applications

181

remedial options. This study shows the practical interplay of key elements of the sustainomics approach in the IPCC process that help to transcend barriers of discipline, space, time, stakeholder viewpoints and operationality, to deal with large-scale, long-term, complex and interlinked issues such as sustainable development and climate change (see Sections 5.1 to 5.4)

6.1.1 Introduction to the IPCC The work of the IPCC addresses the twin challenges of climate change and sustainable development (see Chapter 5). The IPCC was established in 1988 by the World Meteorological Organization (WMO) and the United Nations Environment Program (UNEP), to assess scientific information on climate change, as well as its environmental and socioeconomic impacts, and to formulate response strategies. Under the aegis of the United Nations, the world’s foremost climate experts were engaged in a multiyear process to carry out this task. In 1990, the IPCC’s First Assessment Report (FAR) focused on the science of climate change, concluding that continued accumulation of anthropogenic GHGs in the atmosphere would lead to climate change whose rate and magnitude were likely to have important impacts on both socioeconomic and natural systems. The Second Assessment Report (SAR), in 1995, deepened the analysis on ecological impacts and provided rough estimates of future economic damage as well as mitigation measures. Confirming the FAR findings, the SAR stated that ‘the balance of evidence suggests a discernible human influence on the global climate,’ and predicted a 1–3.5 °C increase in global mean temperature and 15–95 cm rise in mean sea level by 2100. In 2001, the Third Assessment Report (TAR) further confirmed that climate change is inevitable and estimated that the global mean temperature will increase by 1.5–6 °C. The report examined the interlinkages between climate change and sustainable development. This section describes the lessons learned from the multidisciplinary interactions involved during the writing of the TAR, and shows how the integrative, transdisciplinary approach promoted in the sustainomics framework has contributed to the IPCC process. The TAR has three parts, dealing with (1) the science of climate change; (2) adaptation; and (3) mitigation. These parts were prepared by working groups WG1, WG2 and WG3, respectively. Over 500 ‘lead authors’ from a large variety of disciplines and many countries were organized into chapter-writing teams. Climate scientists were in the majority in WG1; natural scientists predominated in WG2; and economists and energy experts were more common in WG3. Furthermore, many thousands of other experts reviewed several drafts of the TAR before it was approved by all national governments.

6.1.2 Guidance paper on development, equity and sustainability The IPCC Bureau (managing the TAR) commissioned guidance papers on several key issues that cut across the working groups and chapters, to ensure consistent treatment. The guidance paper on climate change and sustainable development proved to be a real challenge. Most authors had little prior exposure to the complex sustainable development literature.

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Furthermore, the paper had to be prepared within a few months, to feed into the IPCC process before the writing teams began to draft their chapters. The paper was entitled ‘Development, equity, and sustainability (DES) in the context of climate change’ (Munasinghe, 2000a). The DES paper was built on the sustainomics framework (see Chapter 2). It posed three questions to TAR authors: (1) How will future development patterns and scenarios affect climate change? (2) How will climate-change impacts, adaptation and mitigation affect future sustainable development prospects? (3) How could climate-change responses be integrated better into sustainable development strategies? To examine the circular interaction between climate change and sustainable development, the guidance paper outlined the analytical framework that has already been described in Sections 5.1 and 5.2. Climate-change interactions with sustainable development (including alternative response strategies) could be assessed in a risk management framework, considering long-term effects on: (1) human welfare and equity; (2) the durability and resilience of ecological, geophysical and socioeconomic systems; and (3) the stocks of different kinds of capital (e.g. manufactured, natural, human and sociocultural assets). Specific economic, social and environmental indicators are needed at different levels of aggregation ranging from the global/macro to local/micro. Indicators must be comprehensive, multidimensional, practical and account for regional and scale differences. Among the large array of indicators already available, TAR authors should carefully select those indicators that focus on key attributes of sustainable development. They need to engage in a transdisciplinary, integrative process, which systematically searches beyond the mainstream journals, for the growing volume of literature that addresses the nexus of climate change and sustainable development, especially interdisciplinary. The social, economic and environmental approaches to sustainability must be recognized and reconciled wherever possible (see Chapter 2). Two methods based on optimality and durability are useful in providing an integrated and balanced treatment of these viewpoints (see Section 5.4). Even though a climate strategy cannot address all poverty- and equity-related problems, it would be useful to assess whether climate change will worsen existing poverty and inequity. Climate change and other global environmental issues, such as loss of biodiversity, desertification and stratospheric ozone depletion, are inextricably linked with each other, as well as with more localized environmental problems. One important challenge is to identify ‘win–win’ strategies, which would favour development paths that reduce GHG emissions without undermining prospects for reducing poverty and improving human welfare. Institutional and governance issues would be crucial in implementing adaptation and mitigation measures. It was also emphasized that the TAR would be more useful to decision makers if it was able to incorporate the viewpoints of all stakeholders, including governments, business, civil society and non-governmental organizations.

6.1.3 The internal debate, outcome and lessons learned The first draft of the DES paper was circulated via e-mail to all TAR authors in late 1999, and a spirited debate ensued, unprecedented in IPCC history. It involved natural


183

scientists, economists, sociologists, climate scientists, developmental specialists, environmentalists, geographers, political scientists, general policy analysts and others with mixed backgrounds. The first phase began with a heavily critical e-mail jointly signed by six neoclassical economists, urging that the paper be discarded. They claimed that the role of economics had been diminished, while a new framework was being introduced (linking economic, social and environmental concepts), which did not reflect consensus opinion. In the second phase, many others responded individually (1) broadly supporting the main thrust of the paper; (2) offering specific but constructive criticisms; and (3) rebutting the original six critics. There was general support for the need to bridge disciplinary approaches via the holistic, balanced framework combining economic, social and environmental viewpoints, and for reconciling optimality/efficiency with durability/resilience. Most agreed that the paper outlined a flexible approach, rather than being a straightjacket to force consensus, because it drew attention to the main issues and suggested options to address them. Other comments on the paper included requests for more specific practical guidance to apply the new framework, more details on economic, ecological and social indicators, to assess the sustainability of alternative futures, and many minor technical corrections. Contradicting the neoclassical economists’ criticism, many other authors felt that the paper was overly oriented toward economic efficiency, and that it should focus more on poverty, equity and sustainability issues. The original six critics were also faulted for selectively misrepresenting arguments presented in the paper, exaggerating the role of economics while overlooking its shortcomings and failing to accept the importance of key sustainable development issues relating to poverty, equity and sustainability. They were further criticized for ‘ganging up’ early, to pre-empt and choke off further discussion, and for adopting a ‘hegemonistic,’ confrontational and harsh tone inappropriate for effective scientific dialogue within the IPCC. The final phase was marked by much milder exchanges, many involving second thoughts. A deeper dialogue took place among participants, and many points of agreement emerged. The original six critics withdrew their objections and the DES paper was revised and finalized (Munasinghe, 2000a). Subsequent discussions continued in a collegial and convergent manner, within and across the writing teams of specific chapters of the TAR. Judging the success of this exercise is best left to readers of the TAR. One outcome was that the IPCC process has been further strengthened. Participating scientists ended up with a better idea of each others’ viewpoints, and there was surprisingly little rancour at the end. Minds became more open and the transdisciplinary dialogue improved. Despite differences in academic training, culture and outlook, an underlying sense of fellowship prevailed – that the unique, and hitherto highly successful, IPCC process was indeed worth protecting. Sustainable development issues were explicitly introduced into the TAR and associated documents. However, treatment of sustainable development across chapters remains uneven. Even greater progress could have been made if the early selection process for lead authors had recognized the need for experts with a better grasp of these issues. One key

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outcome was that the IPCC Bureau and the main governing body (the IPCC Plenary) decided to incorporate fully sustainable development as a major theme cutting across all three working groups of the next (fourth) assessment report. What are the key lessons learned from this experience? The sustainomics-based approach proposed in the guidance paper was clearly preferred by the majority of lead authors (except for initial reservations of the small group of neoclassical economists). Thus, transdisciplinary work was considered essential to deal with large-scale, long-term, complex and interlinked issues such as sustainable development and climate change. However, crossing disciplinary and cultural boundaries requires sound knowledge of one’s own discipline (especially its limitations), open-mindedness, great patience and sincere effort on all sides. A heuristic approach is essential to maintain the delicate, dynamic balance between the twin objectives of promoting holistic integration across disciplines and preserving the rigour of individual disciplinary models. The continuing IPCC process has greater value than any single result, because our knowledge is far from complete and constantly evolving. Thus, building good faith and trust (i.e. social capital) among diverse colleagues and understanding different viewpoints are more important longer-term goals than being correct on some specific point. E-mail proved to be a powerful, but potentially risky, tool for quick, broad-based reviews. It was a necessity, given the international scope of exchanges within severe time and resource constraints. However, face-to-face meetings are far less likely to cause ill-feeling in a multidisciplinary, multicultural debate, in which modes of expression vary widely. Often, the ‘tone’ of e-mail dialogues could be misperceived as abrasive, especially when it is not among close friends and colleagues. In such circumstances, how something is said could be as important as what is said, to ensure effective communication. Nevertheless, fairmindedness and good-will finally prevailed, despite some difficult moments. What insights did the debate provide about the resilience of the IPCC intellectual community? This network has already proved to be quite cohesive in the face of determined attacks by powerful and well financed ‘anti-climate-change’ lobbies. The strong pressure to include sustainable development concerns within the TAR was a different kind of external stress. Adaptation and learning within the IPCC community took place in several ways. First, fresh ideas were brought in to catalyse change. Second, the disciplinary mix evolved to meet the challenge (and continues to do so). Third, IPCC internal processes adjusted to facilitate beneficial changes, while limiting harmful dissension. Scientists were able to accommodate different ways of thinking about the problem, as well as new modes of communication (e.g. e-mail), while re-enforcing desirable codes of conduct and behavioural norms (i.e. building social capital).

6.2 Multilevel integration of millennium ecosystem assessment results and millennium development goals In this case example, we examine how a key sustainomics tool, the Action Impact Matrix (AIM), might be used to explore the linkages between two important international initiatives – the


185

millennium development goals (MDGs) and millennium ecosystem assessment (MA) – see Chapters 1 and 4.

6.2.1 Mainstreaming the environment into a sustainable development strategy An important follow-up of the MA is to apply the results and promote sustainable development in the twenty-first century, by generating recommendations on policy, institutional design and governance at the local, national and global scales. Developing linkages and synergies with other international processes, such as the MDGs and multilateral environmental agreements (e.g. UNFCCC, CBC, CMS, CCD, Ramsar, etc.), is especially important. We start from the fundamental premise that measures to protect ecosystems and ecosystem services ultimately must be mainstreamed into conventional development strategy. The comprehensive and far-reaching recommendations proposed by the MA are rather generalized, and exist mainly at the global and regional levels. Recognizing the multiscale dimensions of protecting ecosystem services (ranging from the local to the global levels), and the need to strengthen in-country activities, we should seek to mainstream the broad MA results by integrating them into sustainable development (SD) strategy at the national and local levels, and implementing them on a more disaggregate basis through local communities and individuals. As a parallel second step, the MA findings will also receive more favourable attention from the development community if one could explicitly identify their linkages with global development concerns – e.g. the MDGs. These mainstreaming objectives could be achieved by using the AIM to identify and prioritize key MA–SD policy linkages at both national and global levels (see Chapter 2). National-level mainstreaming through MA–SD linkage National decision makers normally pay attention to conventional development strategies that seek to achieve objectives such as economic growth, poverty alleviation, food security, improved human health and employment. As shown in Figure 6.1, sustainable development is considered a poorly understood aspect of conventional development. In turn, the environment is one component of sustainable development, and finally ecosystems are a single element of the environment. The horizontal arrow shows that the key step in practical implementation of the MA results within a country is to show the interaction between conventional development activities and key ecosystem services, identify priority issues and determine appropriate policy responses in the development domain. Global-level mainstreaming through MA–MDG linkage Figure 6.2 shows how to link key ecosystems identified in the MA report with all the MDGs. These are multiple, two-way interactions. The common pitfall is that the development community tends to restrict linking ecosystems and their services with just one MDG – i.e. MDG 7 dealing with the environment. A recent review of 100 country-level MDG reports concludes that ‘An assessment of the extent to which environmental considerations

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ES

natural environment

SD (social, economic, environmental)

Development – sectors (agriculture, energy, industry, transport, health, etc.) – systems (socioeconomic, ecological, etc.) – cross-cutting issues (poverty, equity, etc.)

ecosystems and their services

Figure 6.1. National-level ecosystems–sustainable development nexus. Ecosystems are a minor element of development strategy. Source: Munasinghe (1992a).

MDGs

MA ecosystems

freshwater systems poverty/hunger primary education gender equality child mortality maternal health AIDS, malaria

marine and coastal systems forests and woodlands drylands island systems mountain systems polar systems

environment

cultivated systems

global partnership

urban systems other systems

Figure 6.2. Global-level mainstreaming. Key MA ecosystems should be linked to all MDGs, not only MDG 7 on environment.


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are integrated into MDG reports other than Goal 7 shows that environmental issues do not receive much attention outside of MDG7…the causal link between environment and other goals is not well recognized or articulated and response systems are not developed’ (UNDP, 2005a). Establishing the MDG–MA integration at the global level will facilitate efforts to make the same linkage at the national level (Schmidt-Traub and Cho, 2005).

6.2.2 Implementing the MA results Key policy-relevant issues Two policy-relevant questions reinforce the main theme of this paper; i.e. the MA results need to be interpreted and incorporated within a broader sustainable development framework. First, is the balance between humans and nature appropriate? It appears that the MA favours the anthropocentric viewpoint, and gives prominence to the relevance of ecosystems for human well-being. This will be helpful in convincing decision makers and stakeholders to undertake some of the difficult policy remedies. Second, is the south–north balance appropriate? The MA process devoted considerable effort to incorporate the southern perspective fairly (e.g. in the recruitment of managers, lead authors and reviewers, case study material, etc.). Nevertheless, more effort is required in the dissemination and implementation phase, to reassure the developing countries. The broad results suggest that: (1) ecosystems and their services are under threat globally, and the poor are most vulnerable to loss of ecosystem services; (2) policy options and measures are available to manage ecosystems, but they will require radical changes; and (3) such management will yield significant benefits for human well-being. The MA highlights an additional fact, which is relevant for the billions of poor people in the developing world – the bulk of the world’s biodiversity resides in the developing countries. Here, two key poverty–equity related questions arise: (1) Who bears the costs and reaps the benefits of exploiting ecosystem services? (2) Who will bear the burden of preserving ecosystem services and benefit from it? On the first issue, the MA states: ‘In many cases, it is the poor who suffer the loss of services caused directly by the pressure put on natural systems to bring benefits to other communities, often in different parts of the world’ (MA, 2005a). If the rich in distant places exploit ecosystem services, and the local poor have to pay the costs, there are obvious equity implications – both international (south–north) and within countries (and, indirectly, intergenerational, as well). On the second issue, poor countries hardly have resources to address more urgent priorities such as poverty and hunger. If preserving ecosystems and biodiversity have global benefits, both efficiency and equity considerations argue in favour of resource transfers to poor countries that will help them to manage their ecosystems better (see Section 5.4.2). Existing mechanisms (e.g. Global Environment Faculty) are not adequate for this purpose. These questions need to be addressed in order to help the international development community and developing country decision makers respond to the urgent MA challenge of

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better ecosystem management, while simultaneously addressing existing priority issues, such as poverty alleviation, against a general backdrop of resource scarcity. Role of the MA conceptual framework Starting from the global framework provided by the MA, specific strategies, policies and measures for implementation need to be generated at the level of individual communities and sovereign nations. Thus, assessing the advantages and disadvantages of ecosystem management, within a national decision-making framework, will be an essential prerequisite for establishing the balance between ecosystem management and other urgent development priorities, and for identifying and mainstreaming key policies for implementation. The MA conceptual framework (see Figure 4.1) clearly shows the circular linkages between human well-being and ecosystem services. The impacts of ecosystem services on development (upper horizontal arrow) may be better understood in terms of effects on the three major elements of sustainable development – i.e. economic, social and environmental. At the global, national and community levels, we need to determine more specifically if these interactions make development more or less sustainable. Then, specific remedial policy options may be determined and implemented to minimize negative effects and enhance positive ones. Win–win policy options that yield both ecosystem and development benefits (social, economic and environmental) are the most desirable. In other cases, scarce resources may need to be shared between ecosystem management measures and other sustainable development needs, through a careful assessment of trade-offs. Key trade-offs may be needed between the present and future, among ecosystem services, among constituents of human well-being and among stakeholders (MA, 2005b). Such a process will also require the engagement of a broad range of stakeholders, through multilevel mechanisms, to build both ownership and consensus for following up on the MA results within specific countries and communities – the AIM is a useful instrument for this purpose.

6.2.3 Applying the Action Impact Matrix methodology The AIM is an integrating and linking tool (see Section 2.4.1), which has several desirable properties identified in the MA – e.g. the deliberative, information-gathering and planning elements (MA, 2005b). It will help mainstream ecosystem issues to make development more sustainable, at both global and national levels. Globally, we could link MDGs with key MA ecosystem services. At the national level, the AIM will: (1) embed ecosystem concerns in the macrolevel national development strategy of a country via the medium- to long-term sustainable development path and (2) integrate ecosystem concerns into the sub-nationallevel development strategy in the short- to medium-term, by making specific ecosystem projects and policies more sustainable. Furthermore, by linking the global, macroeconomic and microlocal aspects of decision making, the AIM approach helps us to coordinate implementation across scales.


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The AIM approach may be used to understand better two-way interactions between (a) development policies and goals and (b) key ecosystem areas relevant to sustainable development. First, the effects of development policies and goals on ecosystems are explored, and then the reverse effects of ecosystems on sustainable development prospects are identified. The AIM approach analyses key economic–environmental–social interactions to identify potential barriers to making development more sustainable (MDMS), including degradation of ecosystem services. It also helps to determine the priority strategies, policies and projects that facilitate implementation of measures to manage ecosystems and restore damaged ecosystem services. A national-level AIM may be generated through a fully participative, consensus-building, multistakeholder, multidisciplinary exercise (see Section 2.4.1). The process may be repeated at a sub-national or community level to fine-tune the analysis. Thus, the AIM process addresses key implementation issues that are recognized in the MA, such as insufficient participation and transparency in planning and decision making, poor integration across decision-making agencies and inadequate access of stakeholders to information (MA, 2005b).

6.3 Using the AIM to analyse MA–MDG links at the national and global levels 6.3.1 Sample application to Sri Lanka at the national level We illustrate this approach by sketching out a preliminary application to Sri Lanka at the national level. The examples provided below are only indicative, and need to be validated by a full AIM stakeholder exercise. The AIM process involves several key practical steps as follows. Step (a): Determine the most important national goals and policies The following goals and policies are important in Sri Lanka: economic growth, poverty alleviation, food security, employment, trade and globalization, budget deficit reduction and privatization (see Section 2.4.1). Step (b): Determine critical ecosystems and services relevant to sustainable development Starting from the broad generic areas identified by the MA under the supporting, provisioning, regulating and cultural categories of ecosystem services (MA, 2003), we use Sri Lanka data to identify the following critical ecosystem-related areas: forests, managed ecosystems 1 (grain), managed ecosystems 2 (tree crops), coastal and marine systems, wetlands and water resources. Step (c): Identify how development goals/policies might affect ecosystems (DE-AIM) The two lists determined by consensus in steps (a) and (b) are used to establish the basic AIM framework (see Figure 6.3). For convenience of presentation, the row and column

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Global and transnational applications Critical ecosystems and services

(S) Status

(1)

(2)

(3)

(4)

(5)

(6)

Forests

Managed ecosyst. 1 (grain)

Managed ecosyst. 2 (tree crops)

Coastal and marine systems

Wetlands

Water resources

–1

0

–1

–2

–1

–1

Dev. goals/policies (A)

Growth

(B)

Poverty alleviation

(C)

Food security

(D)

Employment Trade and globalization Budget deficit reduction

(E) (F) (G)

–2 +2 +1

Privatization

Figure 6.3. Sri Lanka sample AIM. Development effects on ecosystems (DE-AIM). Key: 3 = high; 2 = moderate; 1 = low; minus(−) = negative impact/status; plus (+) = positive impact/status.

headings are given concisely, but the full spreadsheet will contain detailed notes describing each category in further detail. Thus, within each column, all relevant ecosystem services would be considered as sub-categories (not shown for brevity). The row (S) marked ‘status’ is a useful benchmark indicating the current condition of each ecosystem. For example, cell S1 has a value −2 (moderately negative status), because deforestation has reduced forest cover significantly in Sri Lanka and has decreased all associated services. Next, we identify the impacts of national goals and policies on vulnerable ecosystems, as indicated by the direction of the arrows in the top left hand corner. A few shaded cells are selected to show some key effects. The qualitative numbers represent net outcomes due to various impacts, including trade-offs among different ecosystem services. Brief explanations are provided for each cell. Typical examples include the following. (1) Cell B1 = +2: moderate positive effects of poverty alleviation on forests. The poor may exploit forests unsustainably for their survival (e.g. slash and burn agriculture). Poverty programmes promoting sustainable livelihoods will encourage poor people, who depend on natural resources such as forests, to become less dependent, by moving away from marginal lands into other areas. Helping the rural poor through community forestry projects would also restore some forest ecosystem functions. (2) Cell A4 = −2: moderate negative effects of economic growth on coastal and marine systems. Growth may lead to destruction of coastal ecosystems for industry and urbanization, intensive coastal construction, coral and sand mining, depletion of fish stocks, etc. On the positive side, growth may divert population away from vulnerable coastal resources (e.g. increased employment from tourism decreases coral mining), while higher incomes and awareness could encourage conservation. (3) Cell D5 = +1: low positive effects of employment on wetlands. Greater employment opportunities in sectors that do not depend directly on natural resources and biodiversity, especially for the poor rural folk, would decrease their dependence on marginal natural resources, thus helping to preserve wetlands.


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Critical ecosystems and services

(S) Status

(1)

(2)

(3)

(4)

(5)

(6)

Forests

Managed ecosyst. 1 (grain)

Managed ecosyst. 2 (tree crops)

Coastal and marine systems

Wetlands

Water resources

–1

0

–1

–2

–1

–1

Dev. goals/policies (A)

Growth

(B)

Poverty alleviation

(C)

Food security

(D)

Employment

(E)

Trade and globalization

(F) (G)

–2 –3 –2

Budget deficit reduction Privatization

Figure 6.4. Sri Lanka sample AIM. Ecosystems effects on development (ED-AIM). Key: 3 = high; 2 = moderate; 1 = low; minus (−) = negative impact/status; plus (+) = positive impact/status.

Step (d): Identify how ecosystems might affect development goals/policies (ED-AIM) Next, we identify impacts of vulnerable ecosystems on national goals and policies, as indicated by the direction of the arrows in the top left hand corner of Figure 6.4. Again, a few shaded cells provide examples of key issues, and brief summaries of the relevant links are provided in each cell. (1) Cell B1 = −2: moderate negative effects of forest degradation on poverty alleviation. Deforestation would lead to land degradation, causing further negative impacts on poorer groups who depend on natural resources for their livelihoods. A vicious cycle might be established, as evidenced in recent studies of sustainable livelihoods in Sri Lanka. (2) Cell D4 = −2: moderate negative effects of coastal and marine habitat destruction on employment. Employment provided through activities like fishing, prawn cultivation and tourism would decrease due to coastal and marine system degradation. (3) Cell C6 = −3: high negative effects of water resource degradation on food security. Many crops are highly dependent on the availability of water. Decreases in both quantity and quality of water (e.g. due to over-extraction of groundwater or pollution) will undermine food production.

All cell summaries in steps (c) and (d) are usually supplemented by several pages of text giving details of mechanisms involved and citing relevant reports and research studies. Step (e): Prioritize the most important interactions and determine appropriate remedial policies and measures (preliminary AIM) The list of 78 response options in the MA serve as a useful generic starting point. Other Sri Lanka documents, such as the Poverty Reduction Strategy Paper (PSRP), the National Environmental Action Plan (NEAP) and relevant multilateral environmental agreements (MEAs), will help to develop consensus and provide national and sub-national entry points, which facilitate the implementation of measures to address both development and

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ecosystem issues. Practical and political constraints that limit the range of policy options need to be factored in here. Step (f): Perform more detailed studies and analyses of key interactions and policies options identified in step (e) The critical issues, policy options and measures identified in step (e) may be subject to further analysis and research to identify better remedial measures for implementation. A variety of macro-, regional or local models are usually applied to focus on specific questions (Munasinghe, 1994a, 1997, 2002a). This procedure helps us to evaluate country-specific ecosystem management options, selected from the broad response categories listed in the MA – institutions and governance, economic measures and incentives, social and behavioural responses, technological response and knowledge and cognitive responses (MA, 2005b). Step (g): Update and refine steps (c) to (e) – revised AIM The results of the detailed research and analysis in step (f) are introduced into the AIM process to update and refine the information in the cells and begin the next stage of implementing remedial actions (see Section 2.4).

6.3.2 Application to global and sub-global levels The procedure outlined in Section 6.3.1 could be applied to provide a summary of the key two-way interactions between global-level policy goals and ecosystem services. Thus, the AIM rows become the MDGs (global policy objectives), while the columns are the key MA ecosystems, with ecosystem services included as sub-categories (see Figure 6.2). MA and MDG documents provide information to build two preliminary matrices: (1) the effects of MDG on critical ecosystem services and (2) the impacts of critical ecosystem services on MDG. This process will help to prioritize issues, determine and implement policy options, identify areas for further research and ultimately mainstream the MA findings into the MDG implementation process. It is also possible to consider the effects of further stresses imposed by a variety of global-level drivers, such as globalization, trade expansion and climate change, to identify appropriate international policy responses. Furthermore, similar matrices may be constructed to mesh the MDGs with other MEAs, such as climate change (UNFCCC), desertification (UNCCD) and biodiversity (CBD). A recent UNEP sponsored ‘brainstorming’ meeting concluded: ‘Modalities for greater cooperation should include combining Millennium Project Programmes and MEA programmes to bear upon specific ecosystems identified as country priorities … A matrix should be created in order to identify where environmental concerns intersect with initiatives to reduce poverty’ (UNEP, 2005). Analogous exercises may be conducted at the regional and continental levels, as appropriate. For transboundary ecosystems (e.g. Amazon, multicountry rivers, etc.), the AIM application needs to be tailored to fit the relevant resource basin and stakeholder objectives, which may span many countries and communities.


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6.3.3 Conclusions and recommendations The MA has achieved the major objective of bringing to the world’s attention the serious global threats faced by ecosystems and their services, and the potential adverse consequences for human well-being – especially the world’s poor. The following actions are therefore justified: (1) Further dissemination and implementation of the MA results need to focus on interpreting the generic global- and regional-level findings at more geographically disaggregate levels, especially the assessment of the advantages and disadvantages to specific stakeholders, resulting from ecosystem management measures. (2) One key step in this process would be the incorporation and mainstreaming of ecosystem management measures into sustainable development strategy at the global, national and community levels. (3) The AIM methodology is a useful tool for better integrating policy-relevant MA findings within sustainable development strategy, and implementing them at multiple scales (global to local) – especially within specific countries. The AIM may also be applied to integrate issues arising from other MEAs. The AIM participative process will help to build human resource capacity that facilitates practical implementation of the MA results. (4) A number of case studies should be carried out to test and validate the AIM approach in a range of countries. Based on these case studies, the existing MA multiscale sub-global assessments, and other recent literature, an action programme may be developed. The latter will provide practical guidance to decision makers, policy analysts and other stakeholders, in interpreting, mainstreaming and ultimately implementing the far-reaching MA findings, both globally and on a countryspecific basis.

6.4 Dams and development: multilevel, multistakeholder dialogue Large dams have traditionally been analysed and justified on the basis of comparing economic costs and benefits. Among their multiple purposes, hydroelectric power generation and irrigation have tended to provide the dominant benefits. Potable water, fisheries, downstream regulation, flood control and navigation are some of the frequent additional benefits. On the cost side, engineering expenditures have dominated, although environmental and social costs have been highlighted in recent years. One largely neglected social dimension of dam development has arisen from the absence of stakeholder consultations, especially among those who have been most affected – e.g. families that have faced involuntary resettlement due to inundation of their traditional home areas. Accordingly, this case study focuses on the participative (social) aspects of the sustainable development triangle (see Chapter 2), and on transcending boundaries (geographic, stakeholder and operational). The study is based on the follow up to the World Commission on Dams (WCD) and describes a rather unique multistakeholder, multilevel consultative process for dams. We will examine efforts to: (a) promote dialogue to improve decision making on dams and their alternatives at the global, regional and country levels among a wide range of stakeholders; (b) carry out information networking; (c) disseminate WCD materials; and (d) facilitate exchange of ideas on good practices.

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6.4.1 The World Commission on Dams Institutional framework and process The WCD was established in May, 1998, by the World Bank and the International Union for the Conservation of Nature (IUCN), with two major goals: (1) to review the development effectiveness of large dams and assess alternatives for water resources and energy development and (2) to develop internationally acceptable criteria, guidelines and standards for the planning, design, appraisal, construction, operation, monitoring and decommissioning of dams. The Commission used extensive public consultation and funding based on contributions from 54 public, private and civil society organizations. A consultative forum with 68 members from 36 countries, representing a cross-section of interests, views and institutions, assisted the WCD’s efforts. A variety of inputs ensured the comprehensiveness and independence of the review, including: (1) in-depth case studies of eight large dams in five continents, with three country papers; (2) a cross-check survey of 125 large dams in 56 countries; (3) 17 thematic reviews on five dimensions of the debate and a number of working papers; (4) four regional consultations; and (5) 950 inputs submitted by interested individuals, groups and institutions. The report published by the WCD in November 2000 (WCD, 2000) was widely acknowledged as a major contribution, not only to the debate on the benefits and costs of large dams, but also to current rethinking of development decision making in a world deeply affected by accelerating global change. One key recommendation was that decisions on major infrastructure developments like large dams should take place within a framework that recognizes the rights of all stakeholders and the risks that each stakeholder group is asked, or obliged, to sustain. Consequently, when the Commission had completed its work, a WCD Stakeholders’ Forum was convened as a transitional body. The Forum concluded that maximizing the impact of the WCD report required many actions beyond the initiatives of individual stakeholder groups. Accordingly, at the request of the WCD Forum, UNEP set up the Dams and Development Project (DDP) in July, 2001, to promote a multilevel, multistakeholder dialogue that would facilitate the implementation of the WCD findings, especially at the national and local levels. Main WCD findings While the WCD report did not settle all issues surrounding water and energy development, there was general agreement that the rights and risks approach, the five core values and the seven strategic priorities provide a good framework. The five core values stressed are: equity, efficiency, participatory decision making, sustainability and accountability. Based on these core values, the following seven strategic priorities were set out to serve as a framework for the multilevel, multistakeholder dialogue: (1) gaining public acceptance; (2) comprehensive options assessment; (3) addressing existing dams; (4) sustaining rivers and livelihoods; (5) recognizing entitlements and sharing benefits; (6) ensuring compliance; and (7) sharing rivers for peace, development and security. These priorities echo the key role of consultative mechanisms in sustainable development assessment, like the AIM and environmental and social assessment (see Sections 2.4 and 4.3).


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6.4.2 Dams and Development Project goals and organization This section describes the DDP structure and activities that help to organize and manage such a large global consultative process more systematically. Goal The broad goal of the DDP is to promote a worldwide dialogue on improving decision making, planning and management of dams and their alternatives based on the WCD’s core values and strategic priorities. Objectives The mandate of the DDP excludes it from taking positions or making judgements on individual projects. The specific objectives of the DDP are to: (1) support country, regional and global dialogues, building on issues addressed in the WCD report and aiming to engage all stakeholders with emphasis on those not currently involved; (2) strengthen interaction and networking among participants in the dams debate; (3) support the wide dissemination of WCD findings and other stakeholders’ responses; and (4) facilitate the flow of information and advice concerning initiatives relevant to dams and development. General institutional structure The DDP is a UNEP project directed by the Division of Environmental Policy Implementation (DEPI), with its office based in Nairobi, Kenya. The internal structure of the DDP is shown in Figure 6.5. Steering Committee A 14-member multistakeholder Steering Committee (drawn from the Dams and Development Forum) provides advice to UNEP on policy issues, the work programme and activities of the DDP. UNEP is a ‘non-voting’ member and facilitator of the Committee. Dams and Development Forum The Dams and Development Forum (DDF) comprises approximately 120 organizations. The broad range of constituencies represented include the following main categories: affected peoples groups, government agencies (policy), government agencies (projects/ basins), intergovernmental organizations, indigenous peoples groups, non-governmental organizations, NGOs (advocacy), non-governmental organizations (international), organizations working on options/alternatives, professional associations, private sector/industry, research organizations and utility owners/operators. The DDP Forum serves as a sounding board for the work of the DDP and assists in implementation of its activities. DDP Secretariat During 2001–2003, the DDP Secretariat was based in Cape Town, South Africa, with IUCN acting as the implementation agency. From April 2003, the Secretariat was relocated to

196


UNEP Nairobi Executive

UNON administration and finance

DEPI policy and project management

Steering Committee advisory role – providing feedback and guiding UNEP and the DDP 14 members representing the DD Forum

Dams and Development Project (DDP) DDP Secretariat, Nairobi • coordinator • 2 × senior advisors • 2 × associate experts • 4 × support staff

DD Forum 120 independent members vehicle to carry global dialogue on dams forward

wider group of stakeholders

Figure 6.5. Structure of the Dams and Development Project (DDP). Solid arrows show the responsibility links; dashed arrows show the communication links. Source: Munasinghe (2004c).

UNEP in Nairobi. Five professional staff and four support staff currently work in the DDP Secretariat. Financing The original budget of the project was US $3.4 million, drawn from a number of multilateral and bilateral donors, anchored by UNEP. The current aim is to broaden the financial base through other bilateral agencies, industry and the private sector, foundations and NGOs. Partners and network The DDP continues to interface and build contacts with more than 7000 organizations and individuals on the WCD database and to interact with the development partners. In particular, new partnerships are being continuously forged to promote dialogue at national and local levels.


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6.4.3 DDP work programme The work programme contains four main elements, which are being implemented according to documented and established criteria. In executing the work programme, the DDP consults many stakeholders to understand their reactions and incorporate their views. Promoting dialogue The project seeks to catalyse and support efforts by the different stakeholders to consider and discuss the WCD findings and recommendations. Such support is being provided according to criteria established by UNEP with guidance from the Steering Committee. Multilevel, multistakeholder actions undertaken in this area focus on: (1) servicing the DDF in a dialogue at a global level on issues related to dams and the WCD report and supporting the role of the DDF in encouraging the involvement of all stakeholders, including those with reservations on the report; (2) assisting broad-based national or intersectoral processes, workshops and dialogues; (3) supporting such dialogues through financial resources, access to expertise, information materials and examples of approaches used successfully elsewhere; (4) facilitating the financing of multistakeholder processes; and (5) building on the dialogues and assisting in improving guidelines and criteria for dams and their alternatives in accordance with the WCD core values and strategic priorities. Information network The DDP disseminates information, on new or ongoing initiatives undertaken by others, to help interested parties in participating in initiatives relevant to the WCD report, and in gaining access to information, technical support and funding. The project is focusing on: (1) establishing a communications and networking strategy with clearly defined priorities; (2) maintaining and updating an active website on WCD follow-up with appropriate links to other websites; (3) producing newsletters and other information updates to keep abreast of the status of WCD follow-up and implementation and results of various dialogue processes surrounding the report; (4) establishing a ‘help desk’ for stakeholders to find information on issues related to the WCD report and keeping a record of the source and nature of the requests; and (5) documenting reactions to the report. Dissemination This activity ensures that the WCD results are disseminated as broadly as possible and made available in local languages and in formats that would enhance its impact. Key tasks include: (1) distributing the WCD report, overview, CD-ROM, knowledge base and related products, including the views expressed at the Third WCD Forum and other stakeholder responses; (2) overseeing and assisting the translation of WCD materials into different languages; and (3) communicating and coordinating information dissemination at meetings, and facilitating attendance by former Commissioners, senior advisors, etc. as resource persons.

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Facilitating exchange of ideas on good practice The DDP disseminates information on experiences, practices and tools relevant to the use of the WCD report.

6.5 Evaluation of the Dams and Development Project (2001–2004) 6.5.1 Objectives, scope and methodology A comprehensive evaluation of the DDP was conducted by an independent, external evaluator,2 with the objective of determining to what extent the project has been successful in fulfilling its objectives and achieving expected results in a cost-effective manner – by reviewing project impact and the implementation of planned project activities, outputs and outcomes. The evaluation provided the fundamental basis for extending the DDP into a second phase beyond July 2004. The findings of the evaluation were based on the following. (a) A comprehensive survey questionnaire sent to all DD Forum members, the Steering Committee and other key stakeholders. (b) Desk review of the project document and work programme outputs (such as information sheets, forum proceedings, Steering Committee meetings notes, assisted national multistakeholder processes, translations, databases, websites, reports). (c) Twenty-five interviews (in person, by telephone and by e-mail), including 11 Steering Committee members, the Director of the UNEP Division of Environmental Policy Implementation, the Coordinator of the Dams and Development Secretariat, key stakeholders involved in the national dialogue processes and former Commissioners of the World Commission on Dams, DD Forum Members and other staff of the DDP Secretariat. (d) Interviews with key stakeholders involved in a representative case study of the national multistakeholder process on dams and development in South Africa.

6.5.2 Survey results The assessment of the DDP is provided in the following, according to specific performance indicators. The overall evaluation is based on the survey responses, supplemented by information from interviews and written documents. Of the 147 surveys sent out, 42 responses were received – i.e. a high response rate of almost 30%. The findings and rating of specific achievement categories are based on the following approximate weights – survey (50%), interviews (25%), written documents (25%). The final results are quite robust. Changing the relative weights did not significantly alter the pattern of results, since the three main sources of information (survey, interviews and reports) were generally 2

Full and independent access to information was ensured through the cooperation of UNEP’s Chief of Evaluation and Oversight Unit (EOU), the Director of UNEP’s Division for Environmental Policy Implementation (DEPI) and the Coordinator, Dams and Development Project, in Nairobi, Kenya. Criteria for selecting the evaluator included the following: (a) no prior direct involvement with the WCD and/or the DDP; (b) good expertise on the subject matter; (c) good experience with projects of a global nature; and (d) good project evaluation experience.

6 International process applications (K) role of UNEP

2.3

199

2.4 2.7 3.1

(J) monitoring and evaluation

2.9

(I) replicability

2.8 2.9 2.8

3.3

question

(H) country ownership (G) multistakeholder approach

2.9

(F) sustainability

3.8 3.2

2.9

3.2 3.5 3.2 3.3 3.2

(E) financial management

3.1 3.0 3.2

(D) implementation approach (C) institutional performance (B) delivering key outputs and activities (A) achieving four main objectives 0.0

3.3

3.1 3.0

3.0 3.1

2.9 2.7 2.8

2.6

3.0 2.9 3.1

0.5

1.0

1.5

Scoring key 1 = excellently/outstanding 2 = very well/very good 3 = well/good 4 = adequately/satisfactory 5 = inadequately/unsatisfactory

2.0 2.5 3.0 average response

3.5

(90–100% achievement) (75–89%) (60–74%) (50–59%) (less than 49%)

4.0

4.5

5.0

total DDF SC

Figure 6.6. Averaged results of respondents in the Steering Global and Forum Committee (scale of 1 to 5, with lower values indicating more favourable ratings). Source: Munasinghe (2004c).

consistent. However, some differences of viewpoint among various stakeholder categories were found. Survey results given in Figure 6.6 are explained below. (A) How well has DDP achieved planned results with regard to the four broad project objectives? – Good (3). (B) How well has DDP delivered key outputs and activities set out in the project document? – Good (3). (C) How well have different parts of the institutional and administrative framework performed? – Good (3). (D) How successful was the implementation approach? – Good (3). (E) How good is the financial management (to be answered by SC members only)? – Good (3). (F) How sustainable are DDP activities? – Good (3). (G) How well has the multistakeholder approach succeeded? – Good (3). (H) How well has country ownership of activities, policies and processes progressed? – Satisfactory (4) (I) Can the DDP process, multistakeholder approach and institutional setting be replicated? – Good (3). (J) How well have DDP activities been monitored and evaluated, ex-post? – Good (3). (K) How helpful was the role of UNEP in supporting and facilitating DDP activities? – Very good (2).

Averaged survey responses, grouped by different stakeholder categories, are shown in Table 6.1. Overall, the various groups of stakeholders had similar views about the success of DDP. However, there were some divergent opinions. With respect to the success of the implementation approach, research organizations found this aspect to be very good, whereas

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Table 6.1 Responses to survey questions (A) to (K), by stakeholder category Stakeholder category

No of replies A

Affected peoples groups 4 Govt agencies (policy) 3 Govt agencies (proj/basins) 3 Intergovernmental orgs 4 Indigenous peoples groups 3 NGOs (advocacy) 4 NGOs (int) 5 Orgs working on options 2 Professional associations 3 Private sector/industry 4 Research orgs 2 Utility owners/operators 5 Average 42

2.9 3.3 2.7 2.7 3.5 3.2 2.9 3.0 2.6 3.1 3.3 2.9 3.0

B

C

D

E

F

G

H

I

2.3 2.6 2.7 2.8 3.7 2.9 2.9 1.5 2.2 2.9 2.8 3.0 2.7

2.7 2.9 3.3 2.6 4.1 3.2 3.0 2.1 3.1 3.4 2.0 2.7 3.0

2.7 3.7 2.5 2.8 3.7 3.5 3.2 3.0 4.0 2.7 2.0 3.0 3.1

2.8 3.0 2.3 3.2 3.0 3.6 4.3 3.0 4.3 3.3 3.0 4.2 3.2

2.6 3.7 2.8 3.5

2.7 3.8 3.2 3.3 2.8 1.9 2.2 3.5 3.4 2.6

3.2 3.5 3.5 3.8 2.1 4.2 3.1 3.7 2.0 3.5

1.8 3.8 2.0 3.7 4.5 1.9 2.6 1.5 4.0 4.0

J

3.0 2.0 3.0 3.3 3.0 2.7 2.9 2.8 3.2 3.3 4.0 4.2 3.0 2.6 3.0 3.7 3.0 4.1 3.8 4.3 2.8 3.3 3.2 3.0 3.3 2.8 3.1

K 2.7 2.0 1.7 2.3 4.5 3.7 2.8 2.0 1.3 1.0 3.0 2.0 2.4

professional associations indicated a rating of satisfactory. Regarding country ownership of activities, policies and processes, professional organizations found that this aspect was very good, whereas NGOs, private sector/industry and utility owners/operators felt that progress was only satisfactory. Further, views on the replicability of the multistakeholder approach also varied between stakeholder groups. Organizations working on options, NGOs, government agencies (projects/basins) and affected peoples groups found that this approach could be very well replicated, whereas private sector/industry, professional associations and indigenous peoples groups found little potential for replication. Private sector/industry and government agencies (policies) found that DDP activities had been very well monitored and evaluated, whereas organizations working on options rated this aspect as only satisfactory. The role of UNEP in supporting and facilitating DDP activities was found to be very helpful by all stakeholder groups, with the sole exception of indigenous peoples groups, who found it to be bordering on unsatisfactory.

6.6 Dams and Development Project evaluation, conclusions and results 6.6.1 Key lessons learned Multistakeholder process The DDP has sought to disseminate and build on the WCD findings. The core of this effort has been the multistakeholder, multilevel consultative process. After some initial successes, the perception is that this process is now experiencing diminishing returns and delays. Some key trade-offs involve time and substantive content.


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Time requirements Care and patience are needed to ensure the inclusion of all stakeholders and the creation of a balanced and non-confrontational atmosphere for conducting the dialogue. However, this may increase the risk of unduly lengthening the process and losing momentum. Substantive content The initial consensus-building stages of the dialogue tended to focus on less controversial elements of the WCD report (like core values and strategic priorities). However, enthusiasm and credibility will suffer unless the process eventually comes to grips with the more difficult and detailed issues that form the basis for implementable policies within countries. Multilevel experience Global level The DD Forum has been unique in bringing together diverse groups and facilitating constructive engagement and learning from each other. The multistakeholder approach on dams has opened up discussions at many levels. Different viewpoints of multistakeholders on ground situations would have been of great interest and practical value to the parties concerned. Even though the issues are complex, a meaningful and result-oriented dialogue and goals need to be pursued. *

*

*

To maintain interest it is necessary to move beyond the core values and strategic priorities of the WCD and address more substantive, and even controversial, issues. The DDF included a wide range of disciplines and stakeholder groups. However, it was not possible to take advantage of the wide experience of the members in view of the time constraints as well as the problems encountered in servicing a large forum. There is a need for the dialogue to pursue different approaches for new dams as opposed to existing dams. This will promote, for example, emphasis on the application of regulatory instruments and options assessment for new dams, and social and environmental mitigation measures for existing dams.

Regional level *

*

There are built-in advantages and good potential for the development of a regional dialogue, as evidenced by the SADC experience. By holding regional meetings involving both governments and other stakeholders, the SADC had prepared the ground for addressing the problems of lengthy droughts and water sharing in a cooperative manner, within the national context and priorities of concerned countries. The proposal for the DDP to introduce dams and development issues within the regional body covering the Mekong River Basin warrants serious consideration, as it can promote and facilitate a dialogue between both upstream and downstream riparian users. Other regional-level possibilities under consideration include the La Plata River Basin in South America and a GWP South Asia network initiative.

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National level *

*

*

*

The need to focus on national-level dialogue to achieve better and measurable development outcomes has emerged as an important step forward. Activities at national level were constrained due to the dearth of funds, lack of support for capacity building and non-participation of key stakeholders. Multistakeholder participation needs to begin at the early stages. Decision making on dams at the national level (including the DDP dialogue) needs to be closely coordinated, preferably by a key agency with an overarching responsibility in areas for such sectors as energy, water resources and river basin management. The credibility and effectiveness of this local focal point is an essential prerequisite for the success of such dialogues, as otherwise stakeholders can withdraw from the process. Scoping reports that make an assessment of the existing situation can provide the basis for future action, as evidenced by the experiences in Nepal and South Africa. There are great advantages for the national dialogue in working toward integration of dam policy within the national water-resources policy.

Dissemination and information exchange *

*

*

Information networking and dissemination of WCD material have taken place as planned. However, a centralized unit does not have the capacity to reach out to all potential beneficiaries. Assistance in capacity building in national-level agencies will ensure that relevant information will reach even ground-level stakeholders. The information and data collected from individuals and organizations need to be validated. There is a risk of politically sensitive data appearing in databases and websites sponsored by UNEP. A balanced approach is needed in respect of good and bad practice, as people learn as much from failures as from successes. Excessive and unstructured ad hoc information loses its effectiveness. Hence, information should be targeted to specific groups and classified accordingly (e.g. decision makers would prefer executive summaries without technical jargon, whereas experts and researchers would tend to look for more analytical approaches and detailed information in their relevant technical areas).

6.6.2 Overall assessment and recommendations Assessment of DDP first phase During its first phase of activity, the DDP achieved an overall rating of good, corresponding to the range 60–74%, or a numerical value of 3 on the UNEP scale of achievement (see Table 6.2). The rating in each category of the table is based on the survey results summarized in the previous section and Figure 6.6, as well as information from interviews and written documents. The final column of Table 6.2 indicates the correspondence between the survey questions and UNEP achievement categories. DDP achievements in almost all the UNEP designated categories fall into the good range, except for three areas. The attainment of outputs and activities is rated 2, or very good. However, country ownership and cost-effectiveness both are rated 4, or satisfactory. Thus, the following recommendations reflect the need to strengthen in-country activities and reduce the fraction of staff costs in the total budget.


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Table 6.2 Rating of DDP activities by UNEP achievement categories

(a) (b) (c) (d) (e) (f) (g) (h) (i) (j) (k)

Achievement category

Rating

Survey questions

Achievement of objectives and planned results Attainment of outputs and activities Cost-effectiveness Impact Sustainability Stakeholder participation Country ownership Implementation approach Financial planning Replicability Monitoring and evaluation All categories (overall average)

3 2 4 3 3 3 4 3 3 3 3 3

(A) and (C) (B) (E) (A), (G) and (H) (F) (G) (H) (D) (E) (I) (J)

The UNEP rating system used is as follows: 1 = excellent (90–100% achievement); 2 = very good (75–89%); 3 = good (60–74%); 4 = satisfactory (50–59%); 5 = unsatisfactory (less than 49%).

Recommendations Question (A): What are the needs and priorities? Recommendation 1: Dams and development issues will continue to have high priority in many countries, and efforts to address them must continue.

Dams have and will continue to have a major influence on development, increasing the need to make dams more sustainable. This applies equally to the management of existing dams, as well as to the planning, construction and operation of new dams. In particular, decisions regarding dams have to be made by using all available social, economic and environmental, as well as technical, information effectively, and with the involvement of all stakeholders (i.e. it is a multistakeholder process). The DDP has sought to use the multistakeholder, multilevel approach to facilitate implementation of WCD findings regarding core values and strategic priorities. A major achievement has been the creation of an environment for constructive dialogue among stakeholders with widely different views, at various multilevel DDP gatherings. The success of the Steering Committee, the DDF and national processes provide a valuable example that may be replicated elsewhere in the water sector and in other controversial areas where the multistakeholder, multilevel process would be appropriate.

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Nevertheless, the emphasis on engaging all stakeholders at the global level, in a nonconfrontational manner, has been slow and costly, and has not moved beyond the stage of discussing relatively uncontroversial issues. Ultimately, the translation of a global consensus on broad aspects into practical policies, which address more controversial issues and influence decision making within countries, constitutes the crucial element of unfinished business required to maintain credibility and momentum. Recommendation 2: The original DDP objectives need to be carefully reviewed, and fresh priorities determined to support future activities.

While its links with WCD will always be a source of strength, the time has come to move forward, beyond the comfortable umbrella of WCD core values and strategic priorities. Drawing confidence and strength from lessons learned during the first two to three years of operation of the DDP, existing priorities need to be reviewed and revised. While this evaluation report can suggest some general ideas and directions, the in-depth re-assessment of the four original objectives of the DDP, and their relative importance, is an important task for the Steering Committee and Secretariat, as a prerequisite for future DDP activities. One fundamental new direction involves focusing country dialogues and making them more effective from the implementation viewpoint. Many of the more routine tasks, such as translation and dissemination of WCD materials and preparation of good practice examples, may be gradually phased out, farmed out to other institutions, or pursued as a lower priority. Question (B): Who should do it? Recommendation 3: A time-bound extension of the DDP is justified, to realize the benefits of the first phase.

This evaluation has determined that the DDP has made a promising start. Progress has been slow due to many reasons, including the fact that multistakeholder approach is unique and difficult. Nevertheless, the two to three year initial period has provided clear grounds to justify a continuation of the effort. One option would be to extend the DDP for a further two years, but with goals and approaches modified to reflect lessons learned so far. Another alternative might be to phase out the DDP and devolve the more important tasks to other agencies and institutions working on water issues. The preponderance of evidence produced during this evaluation supports a timebounded extension of the DDP, to realize the fruits of efforts made in the past two to three years. A two-year extension would appear to be a reasonable compromise between achieving longer-term goals and avoiding an open-ended commitment. At least the current level of donor funding is recommended to maintain the momentum, coupled with greater focus on high-priority activities, and corresponding streamlining of the Secretariat staff and functions. A re-naming of such an extended activity as the ‘Dams and Development Programme’ would underline a greater focus on processes, policies and long-term goals (since ‘Project’ suggests a shorter-term, product-oriented task). Whatever the title, this activity would retain its status as a project within the UNEP definition.


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Question (C): Where should the Secretariat be located? Recommendation 4: The DDP Secretariat should continue to be located within UNEP.

The general consensus of stakeholder opinions and other evidence indicates that UNEP has played an indispensable and highly positive role in sponsoring the DDP. Its continued support of the DDP will do much to guarantee the success of future activities of the DDP. Thus, UNEP is the clear choice to continue hosting the DDP, given the vital initial role played by UNEP in the WCD process, its past record of support for the DDP, its written commitment endorsing the continuation of the DDP and the existing location of the Secretariat in Nairobi. One compelling argument is the need to avoid another relocation, given the unanimous perception that the move of the Secretariat from Cape Town to Nairobi had already caused major delays and disruption. Concern arose about potential delays that might occur if the DDP was subjected to excessive UNEP bureaucratic procedures. Any decision to relocate within UNEP should be an internal one, to be decided on the basis of where the DDP could derive the most synergistic benefits, while facilitating the mainstreaming of its work into UNEP programmes. Question (D): How might work be better organized and carried out? Recommendation 5: The Secretariat needs to become more focused, streamlined and cost-effective, in line with the revised objectives and priorities (see Recommendation 2). This would include the size and composition of staff and allocation of tasks among them.

Although the Steering Committee has indicated that the financial management has been good, almost two-thirds of the DDP budget is devoted to staff and administrative costs, which is rather high. In parallel with the greater focus on DDP tasks, the Secretariat needs to become more streamlined and cost-effective. The DDP currently has five professional staff positions in Nairobi. Stakeholders feel that staff size and costs have increased since the Cape Town phase of operations, without a commensurate improvement in output. A significant improvement can be made to the composition of Secretariat staff and allocation of functions. The momentum of the DDP cannot be maintained unless the remaining challenges, including a noticeable lack of team spirit and uneven staff performance, are met soon. Assuming an extension of the DDP, the need simultaneously to place more emphasis on country processes, reduce staff costs and keep within budget limitations, will pose a major challenge. The staff composition in particular would need to reflect expertise in multistakeholder processes and multicultural sensitivities. Finally, the relatively small size of the Secretariat, to ensure the essential central coordination, coherence and continuity of activities, will put a high premium on high-quality performance, teamwork and burden sharing. Outsourcing of selected activities needs to be explored. Reducing headquarters staff could be offset cost-effectively by expansion at the regional level – e.g. covering different regions with local consultants or dedicated staff within UNEP regional offices could lower salary costs, travel costs and overheads. Synergies and cost sharing with other departments within UNEP might be exploited better to reduce costs, particularly in areas such as information

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technology, accounting and administration. New technologies such as videoconferencing via the Internet could reduce travel costs and time. Recommendation 6: Country (and regional) processes should be the main focus of future attention, while maintaining the already successful global dialogue at a lower level of intensity.

Dialogue and implementation at the regional and country levels is essential to move forward on the goals and objectives of the DDP. Recommendation 7: DDP functions and resource allocation should reflect the emphasis on country and (regional) processes.

More resources and time need to be devoted to promote in-country (and regional) activities. Greater emphasis at the national level, and more effective follow-up, would help to move the multistakeholder process beyond the stage of discussing generic core values and strategic priorities, toward determining country-specific, action-oriented policy guidelines (starting from relevant WCD best practice guidelines) for action. The country processes should emphasize quality rather than quantity, relying on the examples of successful countries (like South Africa) to encourage replication elsewhere, to disarm suspicions in key countries (especially those with large dams) and to reach out to key countries which so far have not actively participated in the dams and development process. Thus, the DDP Secretariat initially needs to focus on, and work more intensively with, a few key countries (spread across the different regions) that have the greatest prospects for early success in terms of influencing national policy. Better criteria and information (e.g. strong government commitment, highly credible focal point to energize the country process, or prevalence of serious dam issues), are required to identify such high-priority countries. The Secretariat needs to continue the emphasis on inclusiveness and participation of all stakeholders, to ensure ownership and eventual implementation of outcomes. Regional dialogues offer great potential (as shown by SADC). They need to focus on specific issues such as riparian river basin development projects, or sharing of common experiences across countries, to energize in-country stakeholders who might otherwise feel isolated. In general, global-level meetings could be fewer, but better prepared, focused and organized. Both the Forum and the Steering Committee have successfully provided a unique opportunity for divergent views to be presented constructively, and have also raised the profile of WCD findings in the international arena. However, past Forum meetings have tended to be too diffuse and have lacked follow-up (e.g. timely and short summaries of meeting results). Several sensible options to improve the governance, structure, content, frequency and timing of Forum meetings have been discussed at previous Steering Committee meetings, and should be reviewed prior to launching the next phase of DDP activities. The limited time of Steering Committee members could also be more effectively utilized with less frequent meetings, supported by a higherquality, but reduced volume, of documents and information. In summary, the existing


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situation of holding one Forum meeting and two Steering Committee meetings per year should be maintained. The narrowing of geographic focus on country processes needs to be accompanied by a broadening of the context in which dams are viewed. Linking the impacts of dams more broadly with planning for the water-resources sector and the macroeconomy (in relation to the social, economic and environmental dimensions of sustainable development), is especially important to convince decision makers, and helps to complement the wider view offered by the multistakeholder approach. A range of analytical tools, including environmental, social and poverty assessments, the AIM, multicriteria analysis, water-sector models and multisector macromodels could facilitate this process. While constructively synthesizing the diverse views of members to guide both the Forum and the Secretariat successfully, the Steering Committee has sometimes gone beyond its originally envisaged ‘advisory role.’ The future relationship between the Steering Committee and the Secretariat needs to be well thought out in order to maintain the delicate balance between effective guidance and excessive micromanagement. The DDP Secretariat has a key role to play as catalyst, facilitator and advisor to country processes, as well as a clearing house for exchange of information across different countries. In particular, it would be in a good position to initiate a comparative study of different country processes, to learn from past experience (especially South Africa), and identify both generic and country-specific elements. The DDP website has become the core of the information exchange activity, and needs to be maintained cost-effectively. The good (and bad) practice initiative has elicited mixed reactions, because it could provide useful information, but absorb significant resources. A time-bound continuation of this activity within the Secretariat may be the solution, followed by the devolution of the function to another institution. Building capacity within countries to operationalize WCD findings is important. In this context, another DDP contribution that could accelerate the transition from discussions to policy implementation would be the provision of appropriate tools and methods for policy analysis to country teams. Relatively modest funding can go a long way to sustain country processes – especially in the early stages. Dissemination of WCD materials has also proved to be more effective at the country level. The DDP could also improve synergies with other water institutions (globally) and better integrate dam issues into broader water-resources policy (nationally).

6.6.3 Response to evaluation recommendations The independent evaluation of the DDP Phase 1 described above was reviewed thoroughly by UNEP, the DDP Steering Committee, Forum and Secretariat (DDP/UNEP, 2004). Subsequently, all the major recommendations were implemented. Accordingly, the DDP Phase 2 programme was launched in February, 2005, as a two-year time-bound activity. The goal, objectives and work programme were streamlined and revised, based on the evaluation (DDP/UNEP, 2005).

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Goal To promote improved decision making, planning and management of dams and their alternatives building on WCD core values and strategic priorities and other relevant reference materials. Objectives *

*

Support multistakeholder dialogues at country, regional and global levels on improving decision making on dams and their alternatives with the aim of engaging all stakeholders with emphasis on governments. Produce non-prescriptive tools, drawing on all relevant existing bodies of criteria and guidelines for planning and management of dams and their alternatives, which can help decision makers.

To support these main objectives, the DDP Phase 2 work programme seeks to: * *

*

*

strengthen further interaction and networking among participants in the dams debate; disseminate further information on activities, processes and outcomes of national, regional and global dialogues on dams and development; disseminate further, tailored to a country and regional basis, the WCD report and the report of the Third WCD Forum, and make available other stakeholders’ responses; facilitate further the flow of information and advice concerning initiatives relevant to dams and development in partnership with other appropriate organizations.

Specific work programme activities include: (a) promoting dialogue, (b) elaboration of practical tools, (c) networking and communication, (d) dissemination and (e) facilitating exchange of ideas on good practice.

Part III National and macroeconomic applications

7 National economy-wide applications1

In this chapter, the sustainomics framework is used to study the powerful and widespread social and environmental impacts of economy-wide policies (see Section 3.7). Section 7.1 contains a brief review of the historical evolution of ideas linking economywide policies and the environment – starting with the seminal work of Malthus and Ricardo up to modern times. Economy-wide policies (both macroeconomic and sectoral) are often packaged within programmes of structural adjustment, stabilization and sectoral reform, aimed at promoting economic stability, efficiency and growth, and ultimately improving human welfare. Section 7.2 describes empirical evidence, beginning with a discussion of the environmental impacts of structural adjustment programmes since the 1980s, followed by some stylized results. It is the combination of growth and economic imperfections that lead to environmental damage and unsustainable outcomes. Section 7.3 sets out a basic framework for analysing environmental–macroeconomic links. Unforeseen economic imperfections can interact with growth to cause environmental and social harm. Second-best remedial measures could help to limit the damage. In some cases, the timing and sequencing of macroeconomic reform policies could be adjusted to limit environmental and social harm. The standard static IS-LM macroeconomic model may be extended to include environmental concerns. The role of green accounting is discussed. The Action Impact Matrix (AIM) is a key tool for prioritizing environmental–macroeconomic links. A ‘policy-tunnelling’ model shows how complementary policies that eliminate economic imperfections will permit continued growth while limiting environmental and social harm. A case study analysing options for making Brazilian long-run economic growth more sustainable is presented in Section 7.4. Both sectoral and macroeconomic models are used to examine the effects of growthoriented strategies pursued by the government during the past decades, over a range of sustainable development issues such as poverty, employment, urban pollution and deforestation in the Amazon region. Finally, Section 7.5 sets out some concluding remarks, including directions for future work.

1

The valuable contributions of W. Cruz, C. Ferraz, R. Serôa da Motta and C. Young to this chapter are gratefully acknowledged. Some parts of the chapter are based on material adapted from: Munasinghe (2002b), Munasinghe and Cruz (1994) and Munasinghe et al. (2006).

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National and macroeconomic applications

7.1 Historical evolution of ideas This section describes selected macroeconomy–environment work, carried out mainly since the late 1980s, although some historical roots are discernible in several classical papers.

7.1.1 Tracing macroeconomy–environment linkages Early work on such linkages pursued three interwoven lines of enquiry. First, economic activities require natural resources. The key role of land scarcities in limiting growth was shown by Malthus (1798), who stressed impoverishment due to agricultural constraints and exponential population growth. Ricardo (1817) explained how diminishing returns to land would check wealth and population growth. Hotelling (1931) further developed the theory of exhaustible resources (see Section 14.2.1). Koopmans’ (1973) classic paper optimizes a discounted infinite stream of consumption within a (Ramsey-type) growth model (see Section 2.3.2), by combining exhaustible natural capital in Hotelling’s simple model with accumulating stocks of manufactured capital. The macroeconomic interest rate plays a significant role. Subsequent work (Withagen, 1990) explored many ramifications of this approach, leading to work by Hartwick (1990) and others (see following text). Stiglitz (1974) uses a model with capital, labour and natural resources as substitutes in production, to show that higher consumption levels are sustainable, provided increasing technological progress compensates for declining natural-resource stocks. Daly and Cobb (1989) point out that getting macroeconomic policies right may ensure optimal resource allocation, but this work does not address scale issues as economies grow beyond the environmental carrying capacity. Solow (1993) defines net national product (NNP), adjusted to reflect both natural-resource depletion and changes in environmental quality, as a measure of maximum consumption that can be sustained forever. England (2000) identifies three conditions that would lead to a steady-state economy – scarcity of natural capital; complementarity (non-substitutability) between manufactured and natural capital in production; and constraints on technological progress that raises productivity of natural capital use. Recent work has focused on the interactions between sustainable development and long-term optimal growth (Markandya et al., 2002; Munasinghe et al., 2001). The second historical approach draws on input–output (I–O) analysis developed during the 1930s. Leontief (1970) describes a seminal framework to analyse polluting outputs from productive sectors and the impact of policies to reduce such externalities in pollutionabatement sectors. Subsequent studies linked the I–O model with vintage models specifying labour demand and capital stock, and with endogenized consumer demand using linear expenditure systems. Advanced models made the technical I–O coefficients endogenous and dependent on prices. Computable general equilibrium (CGE) models used for macroeconomic–environmental analysis, as well as the integrated frameworks for environmental–economic accounting, use the I–O approach.

7 National economy-wide applications

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Third, environmental considerations have been incorporated into more conventional macroeconomic models, ranging from extensions of the Keynesian IS-LM type used in analyses of comparative statics, to sophisticated CGE models with environmental variables. Environmental considerations are increasingly examined in macroeconomic models, focusing on short-run Keynesian issues such as capacity utilization, unemployment and cyclical movements in the economy. Longer-run environmental–macroeconomic models, for both closed and open economies, are built around supply side issues such as capital accumulation, natural-resource depletion, long-run labour supply, discount rate and rate of technological progress.

7.1.2 Empirical surveys of macroeconomy–environment linkages Grossman and Krueger (1995) question whether an inverted U-shaped ‘environmental Kuznets curve’ describes the empirical relationship between per capita income and several indicators of air and water pollution. Currently, there is agreement that environmental quality declines with increases in per capita income in the early stages of growth, but it is unclear whether continued growth reverses this trend, since the shape of the curve appears to vary widely by country and form of environmental degradation (De Bruyn and Heintz, 1999; Ecological Economics, 1998; Environment and Development Economics, 1997). Opschoor and Jongma (1996) is a comprehensive review of environmental impacts of World Bank and International Monetary Fund structural adjustment and stabilization programmes in developing countries. They confirm the point, made by Munasinghe and Cruz (1994), that using complementary environmental policies to counteract adverse impacts of growth-oriented macroeconomic policies is a short-run remedy, but urge a more integrated approach in the long run. Panayotou and Hupe (1996) point out that using environmental and social policies to cushion the harmful impacts of structural adjustment is second-best, compared with full integration of these policies within the economic reforms. Partial reforms, or incomplete implementation of reforms, may do more harm than good if they are selectively applied without anticipating their social and environmental impacts. Kessler and Van Dorp (1998) draws attention to the unpredictable nature of impacts of structural adjustment programmes and the importance of remediation, focusing on key indicators relating to soils, water resources and forests.

7.1.3 Mathematical modelling Useful qualitative insights about the environmental (and socioeconomic) consequences of macropolicy reforms may be gained with CGE models (Robinson, 1990). Early work by Jorgensen and Wilcoxon (1990) analysed the economic impact of environmental regulations on the US economy using a CGE approach that applies intertemporal analysis to a complex disaggregate model of long-term growth impacts, to estimate the share of abatement costs in total costs for industry and transport. Bergman (1990a) also used a CGE model to simulate the effects of environmental regulation and energy policy in Sweden. Here, the

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environmental market failure is corrected by creating a market for emission permits, which are included in the cost functions. Chapter 9 contains a more detailed review of past CGE modelling work, as well as two case studies (O’Ryan, de Miguel and Miller, 2005; Persson and Munasinghe, 1995). Glomsrod, Monge and Vennemo (1999) use a CGE model to study the impacts of structural adjustment policies on deforestation in Nicaragua. Improving the fiscal balance by reducing public expenditure, or through sales tax reform, promotes economic growth and conserves forests. Some polices increase near-term deforestation, but ease pressure on forests in the longer term. Applying a CGE model to Brazil, Cattaneo (2005) concluded that agricultural growth in the Amazon increases deforestation, whereas technological improvements, for small farms outside the Amazon, raise incomes, improve income distribution and limit deforestation. Innovation in livestock in the Amazon also leads to higher agricultural income, but greater deforestation rates (see Section 7.4.5). Chapter 8 reviews models that examine the sustainability of optimal growth, including a case study by Islam, Munasinghe and Clarke (2003). Holden, Taylor and Hampton (1999) simulate six types of village economies in Zambia to show that structural adjustment policies have significant adverse impacts on the environment. The removal of policy distortions may not lead to well functioning markets, due to high transactions costs and imperfect information in remote areas.

7.1.4 Trade and environment Steininger (1999) provides a comprehensive review of trade–environment models, including Heckscher–Olin, statistical–econometric and applied general equilibrium models, which can address a variety of issues such as leakage, distribution, policy feedback effects, interlinkages between production and markets and specialization patterns. Batabyal (1994) traces impacts of domestic environmental policies on international trade. His theoretical study shows that a large developing country might be worse off by pursuing environmental policies unilaterally. Goldin and Roland-Host (1997) examine the converse question – how growth in international trade might affect the local environment in Morocco (see Section 8.6.3). In their CGE study, trade liberalization alone promotes export-led growth, but increases water stress. When complementary water price increases are simultaneously imposed with trade liberalization, the growth benefits are retained, while water stress improves. Mani and Wheeler (1998) analyse data during 1960–1995 for a variety of industrial sectors and countries. They conclude that trade does not increase production of pollution-intensive goods, since production takes place primarily for domestic markets rather than exports.

7.1.5 Green national income accounting We follow up the discussion in Section 3.7.5 with a brief mention of recent work. Hartwick (1990) derived net national product (NNP) as the current value Hamiltonian for an optimal


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growth problem, including conventional economic inputs and natural resources. To derive NNP, drawdown of natural-resource stocks should be netted out of gross national product (GNP), such as depreciation of economic capital. Repetto et al. (1989) show how Indonesia’s conventionally measured economic output could keep rising, while its naturalresource base is being degraded, unless use of natural-resource stocks is netted out. Hultkrantz (1992) estimates monetary changes in timber stocks, non-marketed and nontimber products and depletion of other natural assets in Sweden. The System of Environmental and Economic Accounting (SEEA) integrated environmental and resource accounting into the standard system of national accounts (SNA) (UN, 1993). Atkinson et al. (1997) describe methods of adjusting the SNA to account for environmental effects, including social accounting matrices. The concept of green national product (i.e. conventional GNP net of changes in environmental services and resources) is extended to develop the idea of ‘genuine savings’ (i.e. national savings net of environmental effects). Aronsson and Lofgren (1998) review developments, provide a theoretical framework summarizing the state of knowledge and set out areas of uncertainty and key questions for further research. A revised version of the SEEA was issued in 2003, describing a satellite system of the SNA that combines economic and environmental data in a common framework and describes their interaction (UN, 2003). It also provides indicators and statistics to monitor these interactions, as well as a database for strategic planning and policy analysis to identify more sustainable development paths (UNCSD, 2005).

7.2 Empirical evidence 7.2.1 Environmental and social impacts of structural adjustment During recent decades, structural adjustment programmes have emerged as a powerful form of macroeconomic intervention in the developing world (see Section 3.4.2). Many developing countries experienced economic hardship during the ‘debt crisis’ of the 1980s. Major oil price increases in 1974 and 1979 were a significant shock to oil-importing countries. Furthermore, restrictive monetary policies adopted by Western countries, to curtail their own inflation, raised real interest rates and made debt-service difficult for developing countries. Thus, developing countries faced balance-of-payment problems, making them even more reliant on foreign donors. Economic growth rates and unemployment worsened. The International Monetary Fund and the World Bank agreed to provide financial assistance to help countries service their debt, provided they adopted broad reforms called structural adjustment programmes (SAPs). These stringent economic and fiscal reform policies, which were designed to restore growth, also had adverse environmental and social impacts. Stabilization policies sought to reduce pressure on foreign reserves by reducing domestic demand. Balance-of-payment problems were addressed by controlling inflation and reducing imports with contractionary fiscal policies and tight money supply. Simultaneously, currency devaluation aimed to improve the terms of trade and make exports more

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competitive. Adjustment policies focused on the supply side and addressed inefficiencies of the internal economic structure, including public sector reforms, to accelerate economic recovery and export growth. Parallel policies were adopted to improve the efficiency of resource allocation and competitiveness of markets at the sectoral level. Unfortunately, these reforms often had recessionary effects, resulting in loss of jobs and livelihoods, before the promised growth could materialize. Budget-cutting pressures also forced governments to abandon social ‘safety-net’ programmes, thereby causing further hardship to low-income groups. Reform programmes have not always achieved their economic goals. Even where macroeconomic gains have been realized through adjustment, environmental and social problems have worsened. Often, economic policies aimed at relieving economic problems undermined the environmental resources and social fabric on which national long-term development will ultimately depend (Munasinghe and Cruz, 1994).

7.2.2 Some stylized results Many case studies exist of environmental and social impacts of country-wide policies (Cruz, Munasinghe and Warford, 1997; Environment and Development Economics, 1999; Kessler and Van Dorp, 1998; Munasinghe, 1996a; Munasinghe and Cruz, 1994; Opschoor and Jongma, 1996; Panayotou and Hupe, 1996; Reed, 1996; Warford et al., 1997; Young and Bishop, 1995). Nevertheless, generalizing about such impacts is difficult, since the links are complex and country-specific. Even the purely economic impacts of SAPs are difficult to trace (Tarp, 1993). However, in the following we seek to summarize some key lessons learned from recent studies. Economy-wide policy reforms have major economic objectives. Their environmental and social consequences fall into three groups – beneficial, harmful and unknown. First are the so-called ‘win–win’ policies, which achieve simultaneous gains in the economic, social and environmental areas. Second, macroreforms may harm both the poor and the environment, unless they are complemented by further protective measures. The third group consists of impacts that are unpredictable because of the complex linkages involved and long-run-time perspective. Beneficial impacts Several studies indicate that liberalizing reforms (such as removing price distortions, promoting market incentives and encouraging trade) often contribute to both economic and sustainability gains. For example, reforms that improve the efficiency of industrial or energy-related activities could reduce waste, increase the efficiency of natural-resource use and limit environmental pollution. Similarly, improving land tenure rights and access to financial and social services will yield economic gains, promote better environmental stewardship and help the poor. Analogously, shorter-run policy measures aimed at restoring macroeconomic stability will generally yield economic, social and environmental benefits. For example, price, wage


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and employment stability encourage firms and households to take a longer-term view, thereby encouraging environmentally sustainable activities. Lower inflation rates not only clarify price signals and enhance investment decisions, but also protect fixed-income earners and the poor. Studies of macroeconomic policies in Zimbabwe and Mexico (Munasinghe and Cruz, 1994) and Thailand (Panayatou and Sussengkarn, 1991) illustrate win–win situations, with both economic and environmental gains. Birdsall and Wheeler (1992) argue that open trade policies in Latin America have promoted both economically productive and environmentally benign modern technologies. Other studies of environmental impacts of macroeconomic adjustment policies have been carried out for Sub-Saharan Africa (Stryker et al., 1989); Thailand, Ivory Coast and Mexico (Reed, 1992); and the Philippines (Cruz and Repetto, 1992). Country studies involving win–win outcomes of sectoral policy reforms cover energy and industry in Mexico (Munasinghe and Cruz, 1994) and Sri Lanka (Meier, Munasinghe and Siyambalapitiya, 1995); water and sanitation in Brazil, China and India (World Bank, 1992b, 1992c, 1993a); and land use in Tunisian rangelands (Munasinghe and Cruz, 1994), Zambian farms (World Bank, 1992d), Brazilian forests (Mahar, 1988; Schneider, 1993), Sudanese forests (Larson and Bromley, 1991) and Botswana pastures (Perrings, 1993). Stabilization policies to control inflation led to more sustainable logging in Costa Rica (Persson and Munasinghe, 1995) and sustainable farming in South America (Schneider, 1994; Southgate and Pearce, 1988). Avoiding harmful impacts Typical economy-wide reform programmes are implemented in stages, with the initial adjustment package targeting the most important macroeconomic issues. Often, some unaddressed distortions (policy, market or institutional imperfections) will combine with an adjustment programme to cause environmental or social harm (Abaza, 1995; Munasinghe and Cruz, 1994). Adverse social and environmental impacts may be avoided by implementing additional complementary measures that remove such distortions without necessarily reversing the original reforms. Some case studies are given in Section 8.6. Other brief examples are as follows. Policy distortions Promotional measures that increase profitability of exports might encourage excessive extraction of an underpriced natural resource (e.g. deforestation of open access areas due to subsidized timber stumpage fees). Similarly, trade liberalization could lead to more wasteful energy-intensive activities in nations with subsidized energy prices. Market failures Successful adjustment may be associated with severe environmental damage – e.g. if external environmental effects of growth (such as air or water pollution) are not adequately

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reflected in market prices. In Indonesia, liberalization and industrial promotion led to less pollution-intensive growth in the modern sector. However, the scale of expansion increased pollution externalities, requiring complementary pollution taxes and environmental regulations (Munasinghe and Cruz, 1994). Institutional constraints Unaddressed institutional problems (such as poor accountability of indebted state-owned enterprises, weak financial intermediation or inadequately defined property rights) undermine sustainable resource management and worsen equity. Thus, reform of regulations and institutions should not lag behind economic restructuring, as shown in the case of energy pricing and institutional reforms in Poland (Bates, Cofala and Toman, 1995). In Peru, economy-wide reforms could have potentially increased harvesting pressures on overexploited fisheries, without complementary laws to protect various fishing grounds included within the adjustment programme (World Bank, 1993b). A study of privatization of property rights and community-based management of estuarine fisheries in India concluded that, even if users initially agree to cooperate and share rents from conservation, significant disincentives will soon emerge, due to lack of well defined property rights (Srinivasan, 2005). Therefore, a combination of state-based and community-based management systems will be required for effective resource management. Short-term stabilization Unless government budget-cuts to bring inflation under control are carefully targeted, they may disproportionately penalize critical expenditures on environmental protection or poverty safety nets (Cornia, Jolly and Stewart, 1992; ECLAC, 1989; Miranda and Muzondo, 1991). Other examples include increases in air pollution in Thailand and Mexico due to reduced infrastructure expenditures (Reed, 1992), adverse impacts on low-income groups in Africa (especially women and children) caused by lowered government spending in areas such as health (Nzomo, 1992), and underfunding of forest protection activities (World Bank, 1994b). Another adverse linkage is the possible short-term recessionary impact of adjustment on poverty and unemployment, whereby the migratory poor are forced to increase their pressures on fragile lands and ‘open access’ natural resources. The remedy would be to expand economic opportunities elsewhere. Fiscal policy Traditional fiscal policies do not favour environmental protection – they place the main tax burden on items such as income, profits and labour. Ecological tax reforms (ETRs) could address this problem by reducing tax rates on environmentally friendly activities and increasing tax rates on ‘bads’ such as resource depletion and pollution. While the former encourages value addition and emphasizes qualitative improvement rather than quantitative expansion (growth), the latter increases resource-use efficiency.


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Longer-term and less predictable effects Economy-wide policies may have unpredictable and counter-intuitive long-term effects on sustainability. Some of these effects may be traced through a general equilibrium analysis that captures both direct and indirect links. The Costa Rica CGE model includes indirect effects on deforestation, to show that economic and environmental impacts of wage restraints in structural adjustment are different from results of partial equilibrium studies (Persson and Munasinghe, 1995); see Chapter 9. Adjustment often succeeds in generating new economic opportunities and livelihoods, thereby alleviating poverty and breaking the vicious cycle of environmental degradation and poverty (World Bank, 1992a). Higher incomes increase willingness-to-pay for better environmental protection. However, while such growth is important for poor nations, it may increase overall pressures on natural resources. Meanwhile, properly valuing resources, increasing efficiency and reducing waste will reshape the structure of growth and limit undesirable environmental impacts. The long-run economic and environmental consequences of adjustment programmes depend on capital and labour mobility. Environmental policies themselves could have impacts on income distribution and employment. Inequitable access to land and rapid population growth exacerbate rural unemployment and income inequality, thereby forcing the poor to depend increasingly on marginal resources for their livelihood (Cruz and Gibbs, 1990; Environment and Development Economics, 2004; Feder et al., 1988; Lele and Stone, 1989). The result is more pressure on fragile environments. A Philippines case study (Munasinghe and Cruz, 1994) evaluates the policy determinants of long-term changes in rural poverty and unemployment that have worsened lowland to upland migration and induced conversion of forest lands to unsustainable agriculture. Shifting cultivation and grazing could worsen land degradation, where capital and technical change are limited and population growth is rapid (Cleaver and Schreiber, 1991). Important long-term links between adjustment programmes, trade and agriculture have been analysed by Goldin and Winters (1992). A study of social security reforms in the USA postulates that, in the current social security system, investments in environmental stewardship may serve as an informal intergenerational contract (Farmer, 2005).

7.3 Framework for analysis 7.3.1 Linking micro- and macroeconomic views of environmental harm – magnitude and structure of growth This section links micro- and macroeconomic analyses. Environmental damage due to the magnitude of growth could be reduced by policy measures that restructure growth – to make it less resource intensive and polluting (see Section 2.4). Munasinghe (1995a) analyses the interplay of price and income effects in an initially stagnant economy that has open access forests. He shows how economic reforms may combine with neglected economic distortions to cause environmental harm.

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National and macroeconomic applications resource price

D1 safe limit (QL )

PEN environmental externality cost (EE)

D0 PEC

economic subsidy (ES) PS Q0 QEN

QEC

Q1

environmental degradation

Figure 7.1. Using pricing policy to restructure growth and make development more sustainable. Source: Munasinghe (1995a).

The downward sloping curve D0 in Figure 7.1, depicts demand for timber, which is assumed to depend on both price P and income Y (i.e. D = D(P,Y)). At the effective (subsidized) price PS, representing the marginal cost of logging, the initial deforestation rate is given by Q0. If QL is the safe limiting rate of deforestation beyond which serious ecological damage occurs, and Q0< QL, the situation may continue undetected and uncorrected. Next, suppose economic reforms stimulate growth and shift the demand curve outward to D1. This ‘income effect’ may result from increased domestic demand (e.g. construction timber) or higher timber exports (e.g. due to trade liberalization and devaluation). Now the deforestation rate could shift to Q1 > QL – causing serious environmental harm. Clearly, the remedy is not to stop growth, but rather to introduce complementary measures that establish proper timber prices. First, property rights could be re-established in open access areas and ‘efficient’ stumpage fees imposed – to eliminate the economic subsidy (ES) and correctly reflect the opportunity cost of timber. The resulting efficient price (PEC) would reduce the logging rate to QEC, which still exceeds QL. Second, an additional environmental externality cost (EE) may be charged to reflect loss of biodiversity or damage to watersheds, and thereby establish the full environmentally adjusted price (PEN). The deforestation rate now falls to QEN < QL. Exactly analogous reasoning would apply if we considered fuel prices and polluting emissions from transport or industry (see Chapter 11). In this case, PS might be a subsidized diesel price, PEC the equivalent trading opportunity cost, PEN the full price including taxes to cover air pollution externality costs and QL the health-determined safety standard. 7.3.2 Modifying macropolicies to avoid environmental harm In this section, we examine whether macroeconomic policies might be directly tailored to satisfy environmental considerations, without using additional complementary measures.

domestic currency appreciation, PD/ePF


221 (Y = YF) N

E

Y > YF B

A

L

CA < 0 D

X (CA = 0)

I

government expenditure, G

Figure 7.2. Timing and sequencing of economic policies to make development more sustainable. PD = price of domestic goods; PF = price of foreign goods; e = exchange rate; IN = internal balance equilibrium; EX = external balance equilibrium; Y = income; YF = full-employment income; CA = current account; AL = reduce government subsidies; AD = depreciate currency/liberalize trade.

Role of second-best policies Maler and Munasinghe (1996) show theoretically that first-best macroeconomic policies that seek a Pareto optimum will not maximize welfare if an environmental externality exists (see Section 8.6). Here, second-best macropolicies ought to be pursued, to trade-off broad macroeconomic goals against environmental damage. Their model confirms both the empirical evidence and microeconomic analysis presented earlier, that environmental damage is indeed caused by the interaction of growth-inducing economy-wide policies with residual imperfections. Therefore, the first-best solution would be to correct the imperfections using complementary policies while pursuing the original macroeconomic reforms. However, if political or other constraints prevent or delay introduction of complementary measures, then second-best macroeconomic policies may be justified – especially in cases where environmental harm could be significant. Second-best options also cover the dynamics of policy reform processes. For example, reforms might be gradually intensified (instead of being suddenly imposed), thereby allowing further time to phase out residual imperfections that degrade the environment. Timing and sequencing of policy reforms Could the timing and sequencing of economic reforms affect the extent of environmental damage? Some insights emerge from the literature on the timing and sequencing of adjustment measures to achieve economic goals (Edwards, 1992; Munasinghe, 1996b). In Figure 7.2, the x-axis indicates aggregate expenditure in a national economy (e.g. government budget, G) and the y-axis reflects the effects of domestic currency appreciation

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(e.g. ratio of domestic goods prices to foreign goods prices weighted by exchange rate, PD/ePE). The line IN represents the internal balance, or equilibrium combinations of G and PD/ePF, which enable policy makers to keep an economy producing at the full employment level YF. The line EX represents external balance, showing the equilibrium when the current account CA is zero (i.e. outgoing and incoming flows of foreign exchange are in balance). Point A represents the initial state of the economy – below the line of internal balance IN and above the line of external balance EX. Typically, macropolicy makers would seek to move the economy toward equilibrium point B by reducing both the current account deficit (since CA < 0) and excess demand for goods and services (since Y > YF), to reduce inflationary pressures. A downward movement AD is achieved by currency devaluation and removal of trade barriers, while a leftward shift AL occurs if government expenditures were reduced – e.g. eliminating subsidies on energy prices. Suppose that reforms affecting AD could be achieved first and AL somewhat later (e.g. because the latter was delayed by powerful transport or industrial lobbies insisting on cheap fuels). Then, economic liberalization represented by AD alone might lead to more foreign investment and growth of energyintensive industries attracted by low energy prices. However, this apparent gain would also result in wasteful use of (subsidized) energy and more environmental pollution. This simple analysis provides useful insights. However, good judgement is required to resist making major changes in economy-wide policies merely to achieve minor environmental (and social) gains. Once again, policy options that achieved ‘win–win’ gains would be the most desirable.

7.3.3 Extending the conventional IS-LM macroeconomic analysis Next, we examine environmental concerns, based on the well-known IS-LM framework used in comparative static analysis of macroeconomic policies (Heyes, 2000). In Figure 7.3, r

E M

I

M1 I1 A

B L

O

L1

S E

S1 y

Figure 7.3. Extending conventional IS-LM analysis to include the environment.


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the familiar IS-LM curves are plotted in (r, y) space, where r is the interest (discount) rate and y is aggregate demand. The IS curve is derived from aggregate demand and supply identity, representing equilibrium in the goods market: y ¼ ½cðyÞ þ iðrÞ þ g ¼ ½cðyÞ þ sðyÞ þ t y; or equivalently ½i þ g ¼ ½s þ t; where c is consumption, i is investment, g is government spending, s is saving and t is the tax rate. Simple calculus yields the basic IS curve: dr ds di ¼ tþ ; dy IS dy dy which is downward sloping. The LM curve is derived from the corresponding money market equilibrium: M=p ¼ Lðr; yÞ; where M is (fixed) money supply, p is the price level and L is money demand. Simple differentiation yields the basic LM curve: dr dL dL ¼ ; dy LM dy dr which is upward sloping. Environmental variables could be introduced into the familiar (r, y) space by examining the variation of environmental capital over time: dðKEÞ ¼ ½eðrÞy þ k KE; dt where KE is the stock of environmental assets, t is time, e is the environmental intensity of economic activity (or pollutants emitted per unit of economic output) and k is the rate of environmental self-renewal in the natural state. In a steady-state economy, d(KE)/dt is zero, and implicit differentiation yields dr ½e ¼ dy EE ½yðde=drÞ: Assume that environmental intensity increases with capital cost, i.e. de/dr > 0. Therefore, [dr/dy]EE is downward sloping. The EE curve is drawn steeper than the IS curve, assuming that e is relatively insensitive to r. Suppose that e is also a function of some regulatory framework parameter Z, which determines how effectively polluters are obliged to pay for

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environmental externalities. If de/dZ < 0, then EE would shift leftward as regulatory enforcement improves. To demonstrate the pedagogic value of this approach, consider an economy initially at equilibrium, with the IS, LM and EE curves intersecting at point A. Expansionary monetary policies would shift the curve LM to L1M1. Restoring the tripartite equilibrium at point B would now require contractionary fiscal policies that yield the countervailing shift IS to I1S1. The EE curve is stable, assuming that it represents a longer-run equilibrium, compared with the short-run shifts in the IS-LM curves. Many similar policy exercises may be conducted, involving changes in various parameters and curves.

7.3.4 Macroeconomic performance measurement issues To include sustainability concerns better in macroeconomic analyses, an improved system of national accounts (SNA) called the System of Environmental and Economic Accounting (SEEA) has been proposed by the United Nations (see Section 3.7.5), and new measures of environmental and social progress need to be developed, as suggested by the MDGs and CSD (see Chapter 1). Gross domestic product (GDP) is the common market-based measure which influences macroeconomic policy. Its shortcomings include neglect of income distributional concerns, non-market activities and environmental effects. Traditional SNA measures do not adequately reflect either the depletion of natural-resource stocks (like deforestation) or environmental damage (due to pollution) (USBEA, 1995).

7.3.5 Action Impact Matrix and tunnelling policies to restructure growth paths The AIM described in Chapter 2 provides a systematic framework for prioritizing and addressing the most important environmental and social impacts of economy-wide policy reforms. The process includes: (1) AIM-based analysis to identify, prioritize and analyse the most serious economic–sustainability linkages; (2) specific ex ante complementary measures to limit environmental and social harm, before economy-wide reforms are implemented; (3) contingency plans and careful monitoring of sustainability issues, to deal with them ex post; and (4) reviewing the timing and sequencing of economy-wide policies and complementary measures, to minimize environmental and social damage. Chapter 2 also set out a model for restructuring unsustainable growth patterns using a ‘tunnelling’ approach – whereby developing countries seeking sustainable development paths could learn from the experience of the industrialized countries and so avoid the same mistakes. Economic imperfections that make private decisions deviate from socially optimal ones, worsen environmental and social damage along some growth paths. Tunnelling through to avoid such harm is possible by: (1) adopting ‘win–win’ policies that provide simultaneous economic, environmental and social gains; (2) using complementary measures to address harmful impacts on sustainability; and (3) reshaping economy-wide policies in cases where environmental and social damage was severe.


225

7.3.6 Areas for further work More country-specific case studies are needed to trace the social and environmental impacts of economy-wide policies – e.g. in areas like trade and privatization. Exploring the sustainability of long-run growth is important, especially in the context of worsening naturalresource scarcities, including global environmental degradation. Better practical models and analytical tools are required, based on approaches familiar to practicing macroeconomists (e.g. extended IS-LM framework). Distributional, political economy and institutional issues also need to be addressed in future work. The cross-linkages between economic, environmental and social impacts of economy-wide policies need to be further explored. Better environmental and social indicators should be developed, including environmentally adjusted national accounts and improved techniques for valuing environmental impacts. Where economic valuation of environmental and social impacts is difficult, techniques such as multicriteria analysis can usefully supplement conventional cost–benefit analysis.

7.4 Case study of Brazil – making long-term development more sustainable In the following sections we present a case study of Brazil to illustrate the generic arguments set out in Sections 7.1 to 7.3 and to show how sustainable development strategies could be devised on a country-specific basis, with due regard for local conditions, resource endowments and social needs.

7.4.1 Introduction Generally, some past economy-wide reforms (including structural adjustment) have been implemented without adequate consideration of their environmental and social, as well as economic, impacts (see Section 7.2). Nevertheless, properly managed reforms could facilitate long-term growth while minimizing environmental harm. More broadly, non-growth scenarios (where poverty and stagnation inevitably lead to unsustainability) are less desirable than growth situations – especially where growth may be restructured more sustainably (see Section 2.5). Hence, one promising approach toward making development more sustainable seems to be the successful implementation of sound economic policies aimed at the recovery or maintenance of growth, combined with the adoption of specific remedial environmental and social safeguard programmes. Appropriate sustainability indicators are a key prerequisite for this purpose. Most importantly, strategies to make development more sustainable must be country-specific. Accordingly, the case study seeks to understand better the links between long-term growth and sustainable development in Brazil, by studying the extent to which growth-inducing economic policies are linked to environmental or social harm, the nature of the mechanisms underlying such interactions and the appropriate policy conclusions to be drawn.

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7.4.2 Economic growth and the challenges of social equity and environmental conservation The industrialization process and growth in income per capita achieved by Brazil since the 1960s has been accompanied by persistent social inequalities and increasing environmental degradation. Until the early 1980s, the Brazilian model of development was based on industrialization through import substitution. Protectionism, development of state companies and ambitious fiscal and credit incentives transformed the previous agrarian economy into a highly industrialized society within 30 years. During the most dynamic period, the 1970s, Brazil grew at an average annual rate of 8.7% and the urban population share increased from less than one-third to about three-quarters of the total population . Nonetheless, this prosperity was not well distributed. About 40% of homes were below the poverty line at the end of the 1970s, and the Gini coefficient for income distribution was 0.60 in 1979, one of the highest in the world (Barros, Henriques and Mendonça, 2000). Low investments in primary and secondary education were key factors perpetuating income concentration. The lack of land-reform policies also led to highly concentrated land ownership. Further, instead of undertaking land reform, the government colonized the Amazon, which caused extensive deforestation. The social inequalities were exacerbated by the oil and debt crises of the late 1970s that generated fiscal imbalances, slowed investment capacity and led to a long recession in the following decade. Rates of unemployment increased and inefficient industrial and agricultural structures were unable to sustain a dynamic growth process. Further, during the 1980s and early 1990s, high inflationary pressures combined with reduced growth opportunities to increase social conflict. In the 1990s, several structural reforms were implemented. Market-oriented policies related to trade and capital liberalization, privatization and deregulation were introduced. As a result, during 1991–1997, foreign direct investment increased by US $14.7 billion and labour productivity in the manufacturing sector increased by 8.7% (Bonelli, 1998). In conjunction with previous policies, restrictive macroeconomic reforms were implemented during the 1990s. The most important was the Real Plan of 1994, which applied a successful monetary stabilization policy that reduced the monthly inflation rate from 80% to 1%. A positive outcome was an immediate income redistribution effect through the reduction of the inflationary tax. The Gini coefficient decreased from 0.58 in 1993 to 0.57 in 1995 (Rocha, 2000), but even this marginal redistribution soon faded due to more unemployment. Other consequences of the Real Plan were massive unemployment, particularly in the industrial sector, and an overvalued exchange rate (resulting from increased external capital inflows to balance the huge current account deficit). High interest rates were partially successful in keeping the external balance under control until 1998, attracting short-term capital investment, but considerably worsening the fiscal balance. In early 1999, the lack of confidence in external stability led to a massive exchange-rate devaluation (which was allowed to float). Subsequently, Brazil has followed a stop-and-go pattern in terms of economic growth, with no sustained pattern of recovery in the 1990s – mainly due to the


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remaining problems of very high interest rates (which depressed productive investments) and substantial current account deficits (which left the exchange rate susceptible to wide oscillations). Meanwhile, social and environmental policies remained less effective than desired. Although social care programmes for the poor in urban and rural areas have been continuously extended, they have not reduced poverty and inequality. The fraction of 10% richest households to the 40% poorer households is about 24 (below 10 in most countries). Similarly, small farms (with less than 10 ha) cover less than 3% of the total farming area, while the share of big farms (with more than 10 000 ha) is above 40%. Agrarian reform programmes have received a large share of the budget, and ambitious targets have been set. Nonetheless, rural poverty remains a serious problem, especially in the northeast of Brazil. Furthermore, rural areas are suffering from serious environmental problems such as water pollution, soil degradation, deforestation and biodiversity loss. Urban regions also suffer from increasing environmental degradation through air and water pollution, lack of sewerage to poorer households and increasing solid-waste generation. Nevertheless, an opinion poll carried out in the late 1990s showed that only 47% of Brazilians agreed with the idea that the environment should take priority over economic growth, and the acceptance of lowered environmental quality in exchange for growth increased among the lower-income classes. Thus, there are major challenges to resuming growth and strengthening the country’s share in the global economy, while reducing social gaps and protecting the environment. This complex analysis was initiated with a preliminary AIM exercise (see Section 2.4.1). Based on the priorities that emerged, we will focus on three specific areas: (a) external trade, industrial growth and pollution; (b) consumption patterns, environment and income classes; and (c) deforestation in the Amazon. The Brazilian economy has experienced successive policy changes to alleviate the pressure on the balance of payments caused by the external debt crisis. In the early 1980s, in order to improve the external account situation, export incentives were created. Indeed, the expansion of the export sector was a key element in the structural adjustment strategy supported by the IMF and the World Bank. This change in the orientation of the industrial policy, so far dedicated to import-substitution, has affected the Brazilian industrial structure. The export-oriented industries achieved a better performance relative to the traditional, domestic-market-oriented industries. In the 1990s, imports expanded steadily due to sustained trade liberalization policies. This import expansion was boosted by the exchange-rate overvaluation after the 1994 Real Stabilization programme. As a result, there was a strong expansion in the use of imported inputs and a reduction in the use of domestic inputs. During the same period, there is evidence that the pollution problem increased, although the index used is an estimate of potential rather than actual industrial pollution. Figure 7.4 shows that the industries with high pollution potential grew faster than the industry average. Thus, industrial growth since the 1980s has been diverted toward potentially polluting industries. The links between pollution potential and trade liberalization were studied by

228

National and macroeconomic applications high pollution potential

total industry

150.0

140.0

1981 = 100

130.0

120.0

110.0

100.0

99 19

96 19

93 19

90 19

87 19

84 19

19

81

90.0

Figure 7.4. Evolution of the Brazilian industry according to its potential pollution. Source: IBGE/DPE/ Industry Department.

analysing the environmental profile of the Brazilian industrial sector using input–output (I–O) modelling and environmental indicators from a survey in the State of São Paulo. In order to capture all industrial pollution generated in industrial processing of manufactured goods, we need to include emission flows from input production to the assembly phase. Such an approach requires an I–O model relating changes in demand vectors to potential industrial pollution levels. The exercise was carried out using the I–O matrices of the Brazilian Statistical Office (IBGE). Four different sets of emission coefficients were used. The first set (CEMA/IPEA) was estimated using pollution emission and abatement data for Brazilian industry in 1988 from the PRONACOP (Brazilian National Program of Pollution Control) project, adapted by Young (1997). The second set was the Industrial Pollution Projection System (IPPS), developed by the World Bank using data from US industry. The third group of coefficients refers to carbon dioxide emissions from fossil fuels consumption in Brazil during 1990– 1994, estimated by COPPE/UFRJ and adapted by Ferraz and Young (1999). Finally, the fourth set of emission coefficients (IPEA-IE/UFRJ) was calculated using emission data of industrial plants recorded in the inventory of the São Paulo State Environmental Protection Agency (CETESB) and value-added data from industrial surveys in 1996. These various data sets incorporate important methodological differences, and all coefficients have shortcomings. The CEMA/IPEA coefficients were estimated using old data from emissions (1987). The IPPS data are based only on air pollutant emissions from fossil fuel consumption and assume that Brazilian industry has the same emissions profile as US industry in the late 1980s. The IPEA-IE/UFRJ coefficients are not derived from recorded


229

Table 7.1 Pollution intensity per unit of output (kg/US $million) Parameter/year

Consumption Investment Exports Total

CEMA/IPEA emission coefficients (kg/US $million), 1995 BOD 1116 453 1370 861 Metals (water) 10 24 47 15 Particulates (air) 3398 8232 8549 4441 SO2 3528 3356 6442 3298 NOx 1672 1574 3029 1603 HC 430 566 880 448 CO 10 899 31 445 55 460 17 855 IPPS coefficients (kg/US $million), 1996 BOD 285 125 276 253 Total suspended solids 3507 8765 13202 5792 SO2 1853 2735 3678 2263 NO2 1127 1304 1562 1218 CO 1683 2347 3410 2037 VOC 825 781 1002 840 Fine particulates 261 717 584 391 Total particulates 501 839 907 619 Metals – land 129 306 453 206 IPEA-IE/UFRJ emission coefficients (kg/US $million) 1996 Organic (water) 903 190 744 744 Inorganic (water) 6.6 7.2 11.5 7.4 Particulates (air) 2388 2794 3667 2634 SO2 934 1151 939 976 0.635 0.281 0.303 0.326 CO2 emissions (kg CO2 per Brazilian Reais), 1994

emissions – instead they use official records of expected emissions (including abatement procedures), assuming that plants operate at the optimal output level. Nevertheless, the results of these I–O exercises showed a consistent result that production associated with industrial exports is more emissions-intensive than production-oriented toward domestic markets (Table 7.1). Thus, Brazilian industry is specialized in supplying potentially polluting goods to world markets. This result is compatible with the hypothesis that developing countries tend to welcome ‘dirty’ industries that are less competitive in developed countries because of tighter environmental controls. Even if export-oriented production is more emissions-intensive for specific pollutants, some domestic-oriented production may also harm the environment. Depending on the methodology used, results may differ for specific parameters, which means that it is necessary to improve data gathering for a better understanding of environmental performance.

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Table 7.2 Difference between export and import emission intensities using IPPS coefficients (g/US $) Pollutant

1990

1991

1992

1993

1994 1995 1996

BOD 0.03 0.03 − 0.01 0.08 0.06 TSS 11.73 11.83 9.37 10.29 8.72 2.10 1.83 1.24 1.64 1.56 SO2 NO2 0.65 0.58 0.33 0.51 0.55 CO 1.93 1.84 1.29 1.63 1.41 VOC 0.28 0.18 0.04 0.14 0.18 Particulates 0.50 0.48 0.37 0.47 0.42 Fine particulates 0.67 0.61 0.45 0.63 0.60

0.14 7.31 1.31 0.42 1.16 0.04 0.42 0.63

0.08 8.23 1.50 0.47 1.33 0.10 0.42 0.63

For two parameters, the output destined for domestic markets are more intensive in emissions (IPEA-IE/UFRJ data for organic and CO2). Thus, there may be no ‘natural’ reason why inward-oriented industrial development would be better in environmental terms. In other words, there is also the need to improve environmental procedures within domestic-oriented firms. For example, promoting environmental certification (e.g. in public procurement procedures), and requiring firms to be in full accordance with environmental requirements (to get access to credit from the official development banks), are key steps toward a more sustainable industry. Emissions ‘savings’ were a positive outcome of imports expansion caused by the trade liberalization process during the 1990s. Since they are produced abroad, imports ‘displace’ the associated emissions to the country of origin – i.e. if imports were produced domestically, emissions would have risen. Using the IPPS emission coefficients for each pollutant in the 1990–1996 period, there was an estimated average change in the associated level of (potential) emissions of 146% (i.e., the ‘savings’ of emissions because of industrial imports increased by 46%). There were differences in terms of pollutants. However, emissions associated with imports would have been greater if rising industrial imports were not concentrated in relatively clean activities, particularly those that are technology-intensive (e.g. electronics). Table 7.2 shows that the emissions intensity of exports (mainly semi-manufactured and intermediate goods) is almost always greater than that of imports. However, the gap in emissions intensity between exports and imports reduced during 1990–1996. Overall, Brazil was a net ‘exporter’ of sustainability, since it traded through the export of industrial goods with higher pollution potential than those it imported. One additional exercise estimated the direct costs of introducing environmental control strategies, combining the methodology proposed by Pasurka (1984), the costs for controlling water emissions (BOD and heavy metals) estimated by Mendes (1994) and aggregate price-elasticities of the exports quantum calculated by Cavalcanti, Ribeiro and Castro (1998). Even in the most pessimistic scenario, the estimated trade diversion caused by


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Table 7.3 Export losses caused by emission control costs (percentage of actual exports) Optimistic scenario (elasticity = −0.34) 1980–1984

1985–1989

1990–1994

1995–1996

0.4% 0.4% 0.6% 0.3%

0.4% 0.4% 0.6% 0.3%

0.4% 0.4% 0.6% 0.3%

Abatement of 100% of emissions Total 0.7% 0.8% Latin America 0.7% 0.7% NAFTA 1.1% 1.4% European Union 0.5% 0.6%

0.9% 0.8% 1.6% 0.8%

0.9% 0.8% 1.5% 0.8%

Abatement of 50% of emissions Total 0.3% Latin America 0.4% NAFTA 0.5% European Union 0.2%

These numbers roughly double for a pessimistic scenario (elasticity = −0.78).

higher abatement costs was relatively low. Thus, the competitiveness of industrial exports would not be greatly affected if adequate environmental controls are introduced (Table 7.3). The highest risks of losing markets are in the footwear, non-ferrous metallurgic and other metallurgic industries. From a more dynamic perspective, the 1996 PAEP field survey of industrial firms in the State of São Paulo showed that firms with international links invest more in cleaner production than domestic firms. This finding is compatible with the hypothesis that trade and capital openness favour environmentally sound practices and products. These results have key implications for policy making. First, the relatively high concentration of industrial exports in pollution-intensive activities makes them sensitive to environmental barriers to trade. If world trade is subject to stricter environmental criteria, Brazilian industrial exports may be at risk. There are two possible strategies to deal with this problem: (1) adopt an aggressive position against the proposed changes in trade regulations, maintaining the status quo of minimal environmental barriers in trade agreements and/or (2) enhance the environmental performance of local industries, either improving emission standards or changing the composition of industrial exports, becoming less dependent on exports associated with ‘dirty’ production chains. The first option reflects a view that environmental restrictions in trade (and capital) flows will not be realized soon. However, if environmental controls are not standardized, and Brazil remains a Latin American leader in this area, Brazilian producers may not be able to compete with exports from neighbouring countries with fewer environmental controls. Thus, the second strategy may be better in dealing with the problem in the long term. There is a consistent trend in Brazilian policy making toward the adoption of economic

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instruments in environmental management, based on the user/polluter-pays principle. Some sectors may face relatively small short-term losses in their competitiveness (except for a few sectors that could receive special compensation during the transition to cleaner production). Many firms are already searching voluntarily for better environmental procedures. This transition toward a more environmentally sound economy cannot however rely on a laissez faire mechanism based on the simple exposure of Brazilian firms to the market. One important step is the push for economic instruments for environmental management, allowing flexible but efficient measures to improve environmental standards. This must be combined with industrial policies aimed at spreading win–win environmental innovations. Some examples of these policies are the strengthening of firms to absorb and generate environmentally related technologies; investment in human capital; reduction in regional differences in environmental performance; incentives for environmental certification; and promotion of environmentally sound products and processes in order to create a domestic market for ‘green’ products.

7.4.3 Urban development, income and the environment Growth, poverty and environmental issues Urban pollution is a severe problem in many Brazilian cities, and the poor suffer most. Serôa da Motta and Rezende (1999) analysed 1980–1990 data linking child-death incidence with the six most common waterborne diseases (intestinal infections, cholera, typhoid fever, poliomyelitis, amoebic dysentery, schistosomiasis and shigellosis). Increasing the provision of public water supply by 1% to unserved homes (earning less than five minimum wages), keeping other sanitation services unchanged, would reduce the number of mortality cases of children under 14 years of age associated with waterborne diseases by 2.5% (462 lives). For a 1% increase in sewage collection and treatment, the equivalent reductions would be, respectively, 1.6% (298 lives) and 2.1% (395 lives). When all three services are jointly provided, the reduction levels would be 6.1% (1139 lives). The investment cost for each life saved related to public water supply is US $115 102, followed by sewage treatment and collection costs that are, respectively, US $175 207 and US $214 562 (Serôa da Motta et al., 1994). When all three services, public water supply, sewage treatment and collection, are jointly expanded by 1%, the investment per life saved is US $164 385. These costs provide one estimate of how much Brazilian society values one poor child’s life. Assuming that sanitation facilities last over 50 years and that operation and maintenance costs are 10% of capital costs, the annualized value of the saved life for the joint alternative is around US $18 000 – over four times the Brazilian per capita income. These figures indicate that impacts of water pollution on human health are significant and that mitigation costs are very high. Serôa da Motta and Fernandes Mendes (1996) determined health costs of air pollution by estimating mortality rates caused by respiratory diseases as a function of meteorological parameters (humidity and temperature), pollution concentration data (particulate and SO2)


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and socioeconomic data (medical care, education level, etc.) for the period 1980–1989. They show that a variation of 10 μg/m3 of particulate matter changes the mortality rate by 1.62%. Using the estimated elasticity, the authors project that a 44% reduction in regional industrial emissions would lead to the level of 50 μg/m3 (which reflects the legal primary ambient standard) and would reduce respiratory-related deaths by 6.4%. Based on foregone output due to illness and premature death, air pollution costs are estimated to be US $1.7–2.2 million. The previously calculated pollution costs are due to increasing urbanization and consumption pattern changes, combined with a very unequal income distribution. Degradation can be highly concentrated in consumption patterns of high-income groups who exhibit high levels of ownership of durable goods, energy and water consumption, sewage and solidwaste generation. However, income constraints drastically reduce the poor’s capacity for defensive expenditures against the effects of degradation (e.g. through better medical care and home environment). Thus, poor people may be bearing the burden of rich people’s pollution. Income distribution and pollution generation Another aspect of income concentration is the unequal impacts of consumption. Recent surveys on household expenditures in Brazil have shown significant changes in consumption patterns in the period 1987–1996. While the population increased by 15% during this period, ownership levels of durable goods among households increased at higher levels. For all income groups, there was a large increase in the ownership of drier machines (173%), freezers (211%) and dishwashers (275%), and an even higher increase arising in the lowerincome groups (IBGE, 1998). These trends led to a more intense consumption pattern based on industrial goods, and consequently a higher energy intensity. The ratio of home energy consumption to GDP increased from 0.049 tonne/US $100 in 1987 to 0.060 tonne/US $100 in 1996 (BEN, 1997). Total residential per capita energy consumption in the period also increased from 0.192 tonne in 1987 to 0.206 tonne in 1996. Nevertheless, per capita residential energy for cooking decreased in the same period, from 0.110 to 0.078 tonne/inhabitant – mainly due to replacement of fuelwood by liquefied petroleum gas. Fossil fuel dominates in the transport sector, while more than 90% of Brazil’s electricity consumption is based on hydro sources. Per capita energy consumption in transport increased from 1.131 tonne/inhabitant in 1987 to 1.348 tonne/inhabitant in 1996. While the energy intensity of agriculture was stable as a function of GDP during the period, the energy intensity of the industrial sector as a function of GDP rose from 0.304 tonne/US $1000 in 1987 to 0.359 tonne/US $1000 in 1997. The fossil-fuel share of energy consumption in Brazil increased by 38% during 1987–1997, mostly due to increases in transport and the substitution of fossil fuels for firewood in cooking. With the diminishing availability of hydro sources, the fossil-fuel share will tend to be higher in the future; 91% of urban households already receive treated water supply,2 but less than 20% of sewage is treated (Serôa da Motta, 1996). 2

Unpublished report by Pesquisa Nacional de Amostra Domiciliar (PNAD), IBGE, Rio de Janeiro, 1998.

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Consumption patterns in Brazil are changing toward environmental-intensive goods and services that increase pressure on the environment. To analyse consumption patterns for urban-income groups in Brazil, we have estimated the household degradation level (E) for each income class estimated by the product of its propensity to degrade (Pmg) and average household income. In turn, Pmg is estimated as the propensity to consume weighted by the pollution intensity of each consumption item. Several scenarios involving progressive and regressive income transfers between income classes were analysed, in order to study corresponding changes in the degradation pressures due to differences in Pmg among income groups. The progressive scenario transfers US $10 billion from the richest classes – equivalent to 7% of their income or 3% of total urban income in Brazil in the year 1995. In the regressive scenario, the poorest classes were expected to lose about US $3.7 billion. Due to data limitations, the analysis covers only two production sectors (industry and agriculture) and three direct services (transportation, water and sewage). The following key environmental linkages are considered: (1) industrial water pollution from organic and inorganic matter and air pollution from SO2 and particulates; (2) agricultural pollution from fertilizer use; (3) household transportation pollution from atmospheric emissions of CO, HC and NOx; (4) household water consumption; and (5) household sewage discharge. The analysis covers urban areas in 1995 that represent more than 90% of national personal income. Industrial pollution is estimated based on I–O modelling of emission flows from the input production up to the assembling phase. The results show that income distribution changes are not strongly linked to significant changes in degradation pressures. In most cases, the richest classes generate as much as 10 to 20 times the degradation of the lowest-income group. At the same time, there is a negative relationship between income and Pmg. The poor tend to degrade more per unit of consumption, mainly due to their high propensity to consume. An inverted U-shaped environmental Kuznets curve is not found for the degradation pressures exerted by different income groups. In sum, variations in propensity to degrade were mainly explained by the greater concentration of income among the rich, and, when applicable, by variations in technological factors among income groups. Second, our estimates show that rich people tend to degrade more than their population share. Lastly, regressive transfers increase degradation and vice versa. In both cases, however, we found that industrial and transport sources show an inelastic relationship between income distribution and total degradation pressure, in which the transferred income share is bigger than the resultant change in share of degradation pressure. High degradation pressure from rich people’s consumption patterns shows another regressive aspect, and raises serious distributive issues: (1) while poor peoples’ consumption is not the main source of harm, they bear more degradation impacts due to inadequate defensive expenditures and (2) as degradation pressure is mainly due to the consumption of the rich, avoiding stricter degradation controls that affect consumption decisions will subsidize rich people’s consumption, at the expense of the poor. Yet, as degradation concentration ratios are lower than the respective income ratios, when degradation control becomes more stringent, poor people will tend to pay more for environmental control per unit of consumption if these costs are passed on through prices.


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Table 7.4 GDP growth and deforestation in the Brazilian Amazon

State Acre Amapá Amazonas Maranhão Mato Grosso Pará Rondônia Roraima Tocantins Amazon region

GDP average growth rate (1985–1997)

Cumulated GDP growth rate (1985– 1997)

Agricultural GDP average growth rate (1985–1997)

Cumulated Agricultural GDP growth rate (1985– 1997)

Growth in deforested area (1978– 1988) (%)

Growth in deforested area (1988– 1998) (%)

4.86 6.72 0.56 1.05

58.31 80.65 6.77 12.56

0.31 11.02 0.50 0.94

3.71 132.20 6.06 11.24

256.0 300.0 1058.8 42.1

65.3 145.3 46.5 10.8

2.91 2.68 4.01 7.20 2.53

34.96 32.17 48.11 86.34 30.41

2.68 5.14 4.57 16.98 0.22

32.13 61.65 54.85 203.82 2.65

257.5 133.2 614.3 2600.0 575.0

84.3 43.2 77.6 114.5 22.2

146.1

45.9

3.61

4.71

Source: INPE (2000); Silva and Medina (1999).

If this regressive aspect is to be avoided, policy instruments need to include compensatory measures. Thus, environmental taxes may be useful since they reduce social control costs and generate revenue that can be recycled within the economy to compensate the poor (see Section 9.1).

7.4.4 Deforestation in the Amazon and production patterns Growth and deforestation trends The Brazilian Amazon comprises an area of almost 5 million km2, of which about 70% is forest, including a major share of known global biodiversity. Deforestation has increased during the past 20 years. About 400 000 km2 of tropical forest were cleared during 1978– 1998 according to satellite data (INPE, 2000). The Amazon also had substantial growth in income per capita. Economic growth was driven by colonization projects coupled with massive infrastructure investments and credit concessions; GDP grew by an average of 15% per year from 1970 to 1980, and the per capita income more than doubled. The economic boom was led by the industrial sector, with an average annual growth rate of 26%, spurred on by the Manaus Free Export Processing Zone. The share of industry in local production increased from 15% in 1970 to 40% in 1980 (Reis and Blanco, 1996). During the 1980s and 1990s, there were substantial growth differences among states. In some states agriculture was the main driver of growth. Table 7.4 shows GDP growth for each

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Table 7.5 Land use in the Brazilian Amazon: 1985 and 1996 (km2) Land use

1985

1996

Perennial crops Annual crops Planted forest Planted pasture Fallow land Productive land not used Total cleared area

10 183.27 79 735.44 3031.78 298 423.46 43 517.64 114 754.61 1 378 194.56

10 788.24 70 604.42 5800.30 477 273.20 29 030.27 74 275.44 1 524 032.00

Source: IBGE agriculture census 1985 and 1995 (includes Maranhão and Goiás).

state of the Legal Amazon from 1985 to 1997, including agricultural GDP growth as a comparator. The most industrialized state, Amazonas, has a low average growth rate, whereas other states, such as Acre and Rondônia, which depend mostly on agriculture, cattle and extraction, had average growth rates exceeding 4%. The states with the highest growth rates, Roraima and Amapá, also had the highest agricultural GDP growth rates. They also had the highest growth rates of deforestation during 1985–1988, confirming that both cropping and cattle ranching cause deforestation. Between 1978–1988 and 1988–1998, the growth of deforestation in the Amazon region decreased. Nonetheless, the deforested area increased during the 1990s in Amapá, Mato Grosso and Roraima, while remaining stable in Acre and Rondônia. Most of the deforested areas were converted to pasture land (Table 7.5). It is found that about 145 837 km2 of land was cleared between 1985 and 1995/96 (close to the value of 174 292 km2 obtained for the area deforested in from 1998 to 1988). The area of planted pasture increased from 298 423 km2 in 1985 to 477 272 km2 in 1996 – an increase of about 60% in 10 years. On the other hand, the area used for crops did not change much. Thus, these results indicate that the conversion of forest into planted pasture is still the main source of deforestation in the Brazilian Amazon. Logging is also an important source of deforestation. The volume of timber extraction increased from about 117 to 523 million m3 from 1980 to 1995, although its rate of growth declined in the 1990s. Poverty and income inequality Despite the significant growth in GDP in many regions of the Amazon, inequality in income and land is strongly present. The Gini coefficient for land in the northern region of Brazil decreased from 0.86 in 1975 to 0.79 in 1985 (Schneider, 1995), but it is still relatively high. Additionally, land and environmental degradation and the lack of rural development have generated a massive migration to urban areas, creating additional problems. The rural share of population decreased from 44% in 1991 to 32% in 2000. The 5.9% annual growth in


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urban population in the Amazon was much higher than the Brazilian mean (2.7% per year). The fastest urbanization occurred in Amapá and Roraima – states which are both agriculture based. Rural-urban migration may be occurring due to unsustainable agriculture and poor living conditions in remote rural areas. Social costs of deforestation Deforestation and environmental degradation in the Amazon imposes social costs, both within and outside its borders. Locally, future growth prospects will be hampered. The conversion of forest into pasture land and crop area is almost irreversible since the soil nutrients are exhausted. Serôa da Motta and Ferraz (2000) show that logging (followed by land conversion to agriculture) does not reflect scarcity and depletion costs. The deforestation process harms other activities as well. In the absence of sustainable forestry practices, the possibilities of future income associated with the use of biodiversity, eco-tourism, carbon sequestration and other environmental services will decrease considerably with deforestation. Biodiversity loss is a major result of deforestation. In 1997 there were 228 fauna species in danger of extinction in Brazil, of which about 90 were from the Amazon (IBAMA, 1997). The Amazon contains several unique ecosystems and species, having both existence and pharmaceutical values (see Chapter 3). Further, predatory logging practices can also cause extinction of valuable commercial tree species, such as mahogany. Martini, Rosa and Uhl (1994) show that of 305 commercially and ecologically valuable tree species, 45 are at risk. Deforestation also causes environmentally related social costs through CO2 emissions. Reis and Andersen (2000) estimated average carbon emissions from the Legal Amazon of 168 million tonnes per year during 1970–1985 (or about 95 tonnes of carbon per hectare cleared). Deforestation and logging are related to the increasing risk of fires in the region. With its humid microclimate, the tropical forest contributes to fire control. Both the selective logging and land-clearing processes greatly increase the probability of fire, particularly because logging opens up the forest canopy (up to 50%) – allowing the sun to dry out leaf litter and other combustible materials. Therefore, deforestation increases the potential for massive ecological and economic losses through accidental fires. Greater frequency and intensity of El Niño events will increase the risk of fires due to drying of forests (Nepstad et al., 1999). Economic incentives and deforestation in the Brazilian Amazon Deforestation in the Brazilian Amazon is a complex phenomenon. The forest conversion process is undertaken by family farmers, large cattle-ranchers, frontier settlers, land speculators and logging companies. Moreover, the process is influenced by markets, as well as institutions and government policies. Therefore, modelling its dynamics is not an easy task. We apply a simple model to annual panel-data for eight states in order to measure the causes of agricultural land clearing and cattle-head expansion in the Brazilian Amazon (Munasinghe et al., 2006): ln yit ¼ a þ b ln pait þ d ln plit þ g ln wit þ l ln crdit þ g ln prdit þ f ln nprdit þ r ln disti þ z ln sdi þ fi þ eit :

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Table 7.6 Determinants of cattle-head density in the Amazon, 1980–1995 Alternative models Independent variables

(1) Fixed effects (2) Random effects (3) GLS-AR

− 0.240 (0.092)a ln(price of cattle-head lagged)it − 0.398 (0.095)a − 0.377 (0.106)a ln(price of pastureland lagged)it − 0.046 (0.076) − 0.080 (0.082) − 0.037 (0.058) ln(cattle credit density lagged)it 0.034 (0.024) 0.062 (0.026)a 0.060 (0.019)a a a ln(paved road density lagged)it 0.307 (0.063) 0.261 (0.064) 0.174 (0.058)a a a ln(unpaved road density lagged)it 0.104 (0.049) 0.210 (0.051) 0.404 (0.046)a a ln(distance to federal capital)i − 0.799 (0.149) − 0.676 (0.100)a a a Constant 3.221 (0.454) 9.168 (1.037) 8.6558 (0.640)a F-test all fi = 0 30.26 Breusch–Pagan LM test for fi = 0 χ2 (1) = 45.66 Prob. > χ2 = 0.0 2 Hausman test χ (5) = 0 Prob. > χ2 = 1.0 N 128 128 128 R2 0.58 Log-1ikelihood 5.144 Dependent variable: ln(cattle-head density). Standard errors are in parentheses. a Variables significant at 5% level. States included in the analysis are Acre, Amazonas, Maranhão, Mato Grosso, Pará, Rondônia and Roraima.

Here yit is the fraction of cleared land in the agriculture estimation or the density of cattle-head in the pasture estimation; pait is the price of output (agriculture products for agriculture and the price of cattle-head for cut in the cattle equation); plit is the price of land (differentiated by crop land and pastureland according to the dependent variable); wit is the rural wage rate; crdit is the rural credit density (differentiated by agriculture and cattle raising credit for each equation, credit/state area); prdit is the density of paved roads (paved roads/state area); nprdit is the density of unpaved roads (unpaved roads/ state area); disti is the distance from the state capital to the federal capital; sdi is the proportion of high quality soil; fi is a specific effect for each state; and "it is the contemporaneous error term. The conversion of forest into pastureland is still the main source of deforestation in the region, but this does not explain why cattle formation has been increasing. Results for both cattle-head density and cleared land fraction are summarized in Tables 7.6 and 7.7. There are two types of factors driving the increasing cattle-head density. First, decreasing prices of land and cattle allowed farmers to increase their stock. The decreasing cattle price is more important than the change in the price of land. Second, government policies,


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Table 7.7 Determinants of cultivated area in the Amazon, 1980–1995 Alternative specifications Independent variables

(1) Fixed effects

ln(price of agric. prod. lagged) ln(price of crop land lagged) ln(rural wage lagged) ln(agric. credit density lagged) ln(paved road density lagged) ln(unpaved road density lagged) ln(distance to federal capital) ln(fraction of high quality soil) Constant F-test all fi = 0 Breusch–Pagan LM test for fi = 0

− 0.007 (0.053) − 0.046 (0.053) − 0.198 (0.115)b 0.060 (0.0266)a 0.273 (0.068a) 0.052 (0.046)

Hausman test N Log-likelihood R2

1.902 (0.331)a 42.71

(2) Random effects a

0.250 (0.084) − 0.048 (0.087) − 0.302 (0.234) 0.247 (0.039)a 0.494 (0.056)a 0.373 (0.047)a 0.246 (0.114)a 0.269 (0.035)a 2.568 (0.914)a

(3) GLS AR 0.117 (0.057)a − 0.129 (0.059)a − 0.149 (0.115) 0.148 (0.034)a 0.425 (0.066)a 0.216 (0.051)a − 0.220 (0.137) 0.390 (0.051)a 6.056 (0.954)a 89.65

χ2 (1) = 108.60 Prob. > χ2 = 0.0 χ2 (6) = 19.86 Prob. > χ2 = 0.003 120 0.34

120

120 2.69

Dependent variable: ln(proportion of crop area). Standard errors are in parentheses. a Variables significant at 5% level. States included in the analysis are Acre, Amazonas, Maranhão, Mato Grosso, Pará, Rondônia and Roraima.

especially credit and road construction, promote cattle-head expansion. While paved roads increased access to markets and decreased transport costs, unpaved roads are also responsible for a substantial portion of cattle-head expansion – probably associated with smaller farmers’ activities (Walker, Moran and Anselin, 2000). The increase in crop area density (although causing less deforestation) is also important, since part of the land conversion process is due to nutrient mining. Farmers first convert forest into crop area and use the soil as much as they can. Then, when productivity has been reduced by nutrient mining, the area is converted to pasture. Changes in the demand for agriculture-cleared areas seem to be more affected by economic variables. Output prices are found to be significant in two of our specifications. Surprisingly, land prices are not important in explaining agriculture land clearing (perhaps due to serial correlation). Rural wages are significant in the fixed-effect model, showing that reduced real rural wages decrease the opportunity cost of going to the frontier, and, at the same time, reduce the costs of hiring temporary labour for land clearing. Analogous to cattle ranching, government agriculture credit is a significant factor in explaining agriculture land clearing.

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Paved and unpaved roads also promote agriculture land clearing, for much the same reasons as cattle ranching. The results emphasize the importance of transport policy in managing future cattle ranching and crop area expansion. The Government Avança Brasil programme (Nepstad et al., 2000) proposed to build a paved road network to foster growth and development in the Amazon, which may worsen deforestation and undermine prospects for sustainable and equitable growth.

7.4.5 Summary of main results and conclusions of Brazilian study In recent years, a wide range of economy-wide policy reform programmes has been undertaken in Brazil. Although these policies are not directed explicitly toward addressing sustainability issues, they may, nonetheless, have significant environmental and social impacts. Even modest progress in recognizing such impacts of country-wide policies will help the design of economic programmes. At the same time, recognition of the underlying policy causes of environmental and social problems will help to make development more sustainable. Industrial growth, external trade and pollution The links between trade competitiveness and the environment are complex, with trade policies having both good and bad impacts. Brazilian industrial exports are more emission intensive than goods produced for domestic markets. This result is compatible with the hypothesis that developing countries tend to accommodate ‘dirty’ industries that are less competitive in industrial countries due to tighter environmental controls. However, this effect was offset by emissions ‘savings’ due to fast growth of imports in the 1990s. By importing goods, the emissions associated with production of those goods are avoided as they are produced abroad. The direct costs of environmental control strategies are relatively low. The export loss due to higher production costs resulting from the control of water pollutants (BOD and heavy metals) would be 1–2% of the total value of Brazilian exports. The footwear, non-ferrous metallurgic and other metallurgic goods sectors face a higher risk of losing markets. Currently, highly polluting sectors risk future market losses in regions where consumers are becoming more environmentally conscious. Export-oriented and/or foreign companies undertake environmental innovations more than inward-oriented and/or domestic firms, due to the higher environmental standards and pressures in international markets. This is compatible with the hypothesis that trade and capital openness encourages adoption of environmentally sound practices and products. These results imply: (1) Brazilian industrial exports may be sensitive to environmental trade barriers and (2) stricter environmental regulation of trade may impose significant export losses. Strategies to deal with this problem include: (1) taking an aggressive stance against the changes in trade regulations to maintain the status quo of limited environmental barriers in trade agreements and/or (2) enhancing environmental performance of Brazilian


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industries, by either improving local emission standards or changing the composition of industrial exports through reduced dependence on exports associated with ‘dirty’ production chains. The transition toward a more environmentally sound economy will depend on: (1) support for capacity building in environmentally related technologies; (2) better dissemination of new technology in the productive sector; (3) improvement of educational and technical skills of the labour force; (4) improvement in the quantity and quality of research centres, linking them to the productive sector interests; (5) specific programmes aimed at reducing regional differences in environmental performance; (6) incentives for certification programmes, including the process of public procurement; and (7) improvement of the domestic consumer’s awareness and perception of the benefits of environmentally sound products and processes, creating a domestic market for ‘green’ products. Urban development, income and the environment In Brazil, there is no evidence of an inverse U-curve linking levels of degradation pressure and income groups, since per household degradation pressure generally falls with income. However, propensities to degrade from urban transportation show this inverse U-shape, due to the great reduction in emission levels of new cars usually owned by rich people. Rich people degrade more than their population share. Regressive income transfers (from poor to rich) increased degradation and vice versa. High degradation pressure from rich peoples’ consumption raises serious equity issues for environmental policy in Brazil: (1) while poor peoples’ consumption is not the main source of degradation, they tend to bear more of the degradation impacts due to inadequate defensive expenditures and (2) as degradation pressure is mainly due to the consumption of the rich, avoiding stricter degradation controls that affect consumption decisions will subsidize rich people’s consumption, at the expense of the poor. Yet, as degradation concentration ratios are lower than the respective income ratios, when degradation control becomes more stringent, poor people will tend to pay more for environmental control per unit of consumption if these costs are passed on through prices. If this regressive aspect is to be avoided, policy instruments need to include compensatory measures. Thus, environmental taxes may be useful since they reduce social control costs and generate revenue that can be recycled within the economy to compensate the poor. Deforestation in the Amazon and production patterns Deforestation in the Brazilian Amazon is a complex phenomenon, involving farmers, large cattle-ranchers, frontier settlers, land speculators and logging companies. Cattle ranching is the main source of forest conversion. There are two types of factors driving the increasing cattle-head density. First, decreasing prices of land and cattle have allowed farmers to increase their stock. Second, the construction of roads has created access to markets and decreased transport costs. Changes in the demand for agriculture-cleared areas are more affected by economic variables – e.g. output prices, rural wages and government agriculture credit. Increased

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labour mobility and decreased costs of transport through construction of new roads lead to more land clearing and timber logging. Paved and unpaved roads also promote agriculture land clearing, for much the same reasons as for cattle ranching. The results emphasize the importance of transport policy in managing future cattle ranching and crop area expansion. Construction of paved roads to foster growth and development in the Amazon may worsen deforestation and undermine prospects for sustainable and equitable growth.

8 Mathematical macromodel applications1

This chapter expands on the generic results of Chapter 7, by exploring two different theoretical approaches to making development more sustainable at the national macroeconomic level. In Section 8.1, we review the literature on the relationship between optimization and sustainability in growth models (see also Section 2.3). Section 8.2 describes the debate on the costs and benefits of economic growth, and outlines methods for making growth models more sustainomics compatible. In Sections 8.3 and 8.4, such a mathematical model is developed to examine the conditions under which development paths focusing on optimal economic growth might also be made more sustainable. The model is numerically solved using stylized data and the results are analysed. The second case is developed, in Sections 8.5 and 8.6, around a theoretical model, which looks at the circumstances that may justify the use of second-best adjustments to macroeconomic policies, in order to counteract economic distortions that cause serious environmental harm. Three case studies of Botswana, Ghana and Morocco show how macroeconomic polices might harm the environment, and appropriate remedial measures are discussed.

8.1 Optimal growth models and sustainable development The economic dimension of sustainable development (e.g. GNP growth) has long been pursued as a major objective. Traditional development based on growth theory has relied on the paradigm of economic efficiency and dynamic optimality. Growth models that optimize economic output are unable to guarantee sustainability (especially environmental and social). By contrast, assessing the economic, environmental and social sustainability of growth does not ensure that economic growth is maximized (Munasinghe, 1992a). We explore optimality–sustainability issues by using a quantitative ecological growth model that assesses the long-run prospects for sustainable economic growth (Islam, 1998). The approach values all costs and benefits of growth (including environmental and social aspects) to the extent possible, and maximizes the resultant net benefits (i.e. benefits minus costs) using conventional cost–benefit analysis. Side constraints may be imposed, especially to ensure ecological sustainability. The results help to evaluate alternative growth strategies and explore policy options that can make optimal growth more sustainable. 1

The valuable contributions of M. Clarke, S. K. N. Islam and K. G. Maler to this chapter are gratefully acknowledged. Some parts of the chapter are based on material adapted from Islam et al. (2003), Maler and Munasinghe (1996) and Munasinghe (1996a).

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Next, we survey growth and sustainability issues. Then a quantitative model is developed to explore this nexus. The results show that concerns about the unsustainability of perpetual economic growth are justified.

8.2 Economic and non-economic costs and benefits of growth The existing literature in this area has limitations. First, most studies are qualitative rather than quantitative. Few authors focus on costs and benefits within an ecological model (Islam, 1998). Second, the impacts on the three domains are generally not distinguished. Economic growth can affect the social or environmental domains in different ways. Sustainability depends on which type of costs and benefits are considered (Munasinghe, 1992a). Recent studies suggest that the costs of economic growth are higher than its benefits (Daly and Cobb, 1989; Diefenbacher, 1994; Islam, 1998; Rosenberg and Oegema, 1995), but others disagree (Beckerman, 1994; Gylfason, 1999). Although macroeconomic planning based on cost–benefit analysis has been proposed (Malinvaud, 1979), it has not been widely implemented (Islam 1998; Van den Bergh 1991, 1996). Thus, a practical growth model that included costs and benefits is needed.

8.2.1 Linking sustainability with costs and benefits of growth Following the Second World War, economic growth was considered vital for improving both individual and collective welfare (Beckerman, 1974; Dodds, 1997; Eltis, 1966; Gyfason, 1999; Hufschmidt et al., 1983; Manning and de Jonge, 1996; UN, 1992). The pursuit of higher incomes dominated environmental and social concerns. However, environmental and social harm can limit long-run growth (see Section 2.5.3). Munasinghe et al. (2001) provides a comprehensive review. Some authors cite the environmental Kuznets curve (EKC). Growth induces pollution, but once society becomes richer additional resources would be expended to reduce pollution to acceptable levels; see Section 2.5.2 (Beckerman, 1992; Gylfason, 1999; World Bank, 1992b). Likewise, as resources become scarcer, market prices would increase to prevent natural-resource exhaustion by encouraging shifts to substitutes and through technical improvements that increase resource supply or reduce usage. In addition, previous predictions of resource exhaustion had proven incorrect. The alternative view was that total costs of economic growth outweigh benefits, resulting in uneconomic growth (Daly, 2000) or impoverishing growth (Islam and Jolley, 1996). Some researchers reported that benefits of growth accrued to richer groups, whilst costs fell mainly on the poor (Adelman and Morris, 1973; Ahluwalia, 1975; Duloy, 1975; Fields, 1995; Munasinghe, 2002a). Thus, despite worldwide economic growth, over one billion people still live in absolute poverty (see Section 1.2). The EKC idea also has been challenged (Ayres 1996; Grossman, 1995). A simple growth-maximizing model might value all costs and benefits (including environmental and social aspects) and optimize the resultant net benefits using conventional cost–benefit analysis (CBA), see Section 2.3.2. When environmental and social impacts

8 Mathematical macromodel applications

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cannot be monetarily valued, non-monetary indicators may be assessed using multicriteria analysis (Munasinghe, 1992a). Sustainability would be ensured by side constraints such as non-negative net environmental degradation and non-declining income, consumption or welfare. A key question is whether there is an absolute limit on economic growth imposed by ecological (and social) constraints (Islam, 1998).

8.2.2 Making macromodels more sustainomics compatible Next, we outline how to integrate social and environmental considerations into macromodels. Such sustainomics-compatible models need to explore several interlinked aspects, including resource depletion, environmental degradation and sustainable economic growth, features of the sustainable growth process, efficiency and fairness in intertemporal allocation of natural resources, social discount rate, the relative importance of different variables affecting the growth rate of the economy, issues of savings, investment, technical progress and input substitutability in production. These models could prove useful in formulating integrated economic, social and environmental strategies for countries. Specific policy issues that a sustainomics-compatible model can address include natural-resource management, expenditure for education, research and development, incentives for investment in physical capital relative to investment in naturalresource-intensive industries and pollution-control strategies. The model results could also generate future trajectories showing the growth path of key variables in the model, e.g. GDP, consumption, pollution, technical progress, capital and population. The model would compare optimal values over the past with actually observed values, and thus provide useful information about the operation, performance and evolution of the environmental–socioeconomic system. A standard economic growth model may be made more sustainomics compatible by (a) capturing the underlying environment–economic interactions in the equations and (b) incorporating sustainability criteria in the objective function. We discuss below how these modifications are incorporated in both continuous- and discrete-growth models. Theoretical (continuous) models include Hamiltonian-based models of social welfare that can be used to investigate the sustainomics approach. Here, social welfare is generally measured in terms of pure economic variables, such as income or consumption, with sustainable growth being ensured by non-declining consumption or capital over time. Islam and Craven (2001) develop mathematical models and computational methods relevant for sustainomics-compatible models, and show that this process requires substantial extensions to traditional models. Applied large-scale discrete sustainomics-compatible models show the crucial relationships between capital accumulation, technical progress, the environment and economic growth. They can also capture continuous growth of the economy caused by increases in capital stock, population and technical progress, subject to constraints imposed by the accumulation of pollution and decline in the stock of natural resources. Many solution algorithms are available to run these models; (see, e.g., Amman, Kendrick and Achath (1995), Barro and Sala-i-Martin (1995), Craven and Islam (2003), Fox, Sengupta and Thorbecke (1973), Schwartz (1996) and Sengupta and Fox (1969)). Specific computer

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programmes include GAMS (Brooke et al., 1997), DUAL, MATHEMATICA (Amman, Kendrick and Rust, 1996), OCIM (Craven, 1995), RIOTS (Schwartz, Polak and Chen, 1997) and SCOM based on MATLAB (Craven and Islam, 2003).

8.3 An optimization model: Ecol-Opt-Growth-1 This section outlines a basic sustainomics-compatible model, and shows how it can be implemented and used for policy analysis and forecasting.

8.3.1 Sustainomics-compatible optimal-growth model Optimal-growth models have been used widely to study issues in growth economics (Ayres, 1998; Faber and Proops, 1990; Perrings, 1987). These models have growth-directed objective functions and can be used to study the ecological sustainability of growth-optimization policies. Optimal-growth frameworks represent the mechanism and processes of economic growth in both descriptive and normative senses (Burmeister and Dobell, 1970). They can incorporate the qualitative and quantitative aspects of growth by including ecological and normative judgement factors in the model. Others (Snower, 1982) have also stressed the use of optimization models in environmental economic studies. Ecol-Opt-Growth-1 (developed in Islam (1998, 2001a)) is a dynamic optimal-growth model with ecological constraints (Cesar, 1994; Faucheux et al., 1996; Pearce and Turner, 1990). It is based on optimal planning theory and includes an optimal-growth program (Chakravarty, 1969; Heal, 1973). The descriptive part, constraints and data set of the EcolOpt-Growth-1 model draw heavily on a dynamic ecological–economic model developed by Van den Bergh (Van den Bergh, 1991, 1996; Van den Bergh and Nijkamp, 1994). At the same time, the descriptive part and constraints set of the Ecol-Opt-Growth-1 model extend the Van den Bergh model by adding 12 more equations, for economic ratios, damage indicators and costs and benefits of abatement and economic growth (see Appendix A, Section 8.7). The model assumes that social welfare is a function of consumption and environmental quality. In the optimal-growth framework, the social planner maximizes intertemporal social utility by choosing optimal paths for consumption, investment and pollution-abatement variables. In the basic Ecol-Opt-Growth-1 model outlined below, the goal is to find optimal trajectories of the growth path for extraction, environmental quality and consumption in an economy that maximizes social utility subject to ecological–economic constraints. Resource use affects environmental quality, which in turn affects utility directly and also indirectly through its effect on production and resource regeneration. This model establishes key links between social welfare, consumption, capital accumulation, technical progress, ecology and economic growth in a growth-maximizing framework. Growth is determined by (a) capital; (b) technical progress due to government expenditure for R&D, education, learning by doing and accumulation of knowledge in the private sector; (c) population; and (d) environmental quality, which is affected by pollution, government spending on environmental control and resource use.


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8.3.2 Ecol-Opt-Growth-1 model General conceptual version of the optimal ecological model, data, boundary conditions and transversality The model is summarized in Section 8.7 – see Islam (1998) for details. Most of the data for the model were obtained from Van den Bergh (1991), except for data related to the objective function and transversality conditions. In some model runs using different economic constraints, such as Cobb-Douglas objective and production functions, additional values of coefficients were specified. While the model data are illustrative, values of parameters and boundary conditions are realistic (Van den Bergh, 1991). A pure time preference of 3% was used, in conformity with the mainstream view on intertemporal preferences of society (see Section 3.6). However, the total discount rate was 3% plus the economic growth rate, as the utility function incorporates log consumption as a variable. The model was also solved with a zero social discount rate, based on the argument that it ensures intergenerational equity and is consistent with social contracts of the individual– government relationship, and that society as a whole should have a higher savings rate than individuals because of the external benefits of public savings and the isolation paradox. Key characteristics of the model are that (1) it is based on a holistic view of development with elements of social choice, ethics and political economy (Dopfer, 1979); (2) it is a multisectoral total ecosystem growth model; (3) it includes social and environmental constraints and feedbacks; (4) it represents an equilibrium ecosystem in the initial period, which can lead to disequilibrium depending on the growth process; (5) it analyses an idealized economic system rather than defending a specific growth theory (Burmeister and Dobell 1970); (6) it has key variables that are determined endogenously; and (7) it models issues of intertemporal equity through the social discount rate and values of variables and parameters. Besides conventional utility functions, some new ones including net benefits of consumption are also specified in this model. The damage functions are based on Nordhaus (1994). The issues of social choice appear in the form of constant constraint optimization, and its components are: (1) objective function (social choices); (2) constraints (underlying the socioeconomic system); and (3) social time preference (intergenerational equity). Ethical views are captured by the discount rate, terminal conditions, sustainability indicators, cost–benefit equations and some parameter and data values. Environmental concerns are represented by constraints on resource exhaustion and resource extraction equations, while social concerns are included via objective functions, social constraints, sustainability indicators and cost–benefit constraints. A useful classification of variables might be as follows: (1) policy target variables (consumption, social and environmental quality, GDP); (2) policy tool variables (sector investments, pollution abatement, resource extraction, R&D expenditure, environmental regulations); and (3) all other variables. First, we empirically study the sustainability of growth in an idealized system, and then we progressively modify different components to reflect real-world conditions. Growth impacts in the model include: standard of living (GDP, consumption), environmental benefits of lower pollution, lower rates of resource destruction and reduced total environmental damage. The

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costs include exhaustion of natural resources, over-utilization of non-renewable resources, pollution accumulation, total environment damage and increased abatement costs. This model is more sustainomics compatible than conventional optimal growth models because (1) it represents environmental and economic systems better; (2) it focuses on specifying an ecological model within an optimal-growth framework; (3) it is solved for optimal trajectories over the planning period by the non-linear programming method, unlike other models that are solved for their steady-state values; and (4) it uses unique computer algorithms and data sets.

8.3.3 Model specification and results of calculations Ecol-Opt-Growth-1 was solved for 11 sets of specifications. Each model spans eight periods, one period being equivalent to 10 years duration. The major differences in these models (see Table 8.1) are based on variations in their objective functions, production functions, time preference rate, etc. Model runs 1 to 9 are based on the optimal-growth model, while model runs 10 and 11 are forecasting models without an objective function. Only model runs 8, 9 and 11 did not have any feasible solutions. Growth and ecological scenarios The model results yield a set of ecosystem scenarios over the planning period that meet the static and dynamic efficiency conditions of resource allocation; see Tables 8.2 and 8.3 and Figures 8.1 to 8.5.

Table 8.1 Different model specifications and runs

Run Model type

Objective Production Investment function/ function function Variable

Pure time pref. (%) 3 3 3

3 − −

1 2 3

optimization optimization optimization

1(a) 1(b) 1(a)

2(a) 2(a) 2(b)

4 5 6

optimization optimization optimization

1(c) 1(d) 1(d)

2(a) 2(a) 2(b)

7 8

optimization optimization with non-declining environmental quality optimization with no abatement forecasting forecasting without abatement

1(a) 1(a)

2(a) 2(a)

sectoral/aggregate sectoral/aggregate aggregate investment as a control variable sectoral/aggregate sectoral/aggregate aggregate investment as a control variable sectoral/aggregate sectoral/aggregate

1(a) −

2(a) 2(a) 2(a)

sectoral/aggregate sectoral/aggregate sectoral/aggregate

9 10 11

3 3 3 0 3


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Table 8.2 Optimal values of policy variables and cost–benefit analysis Period Run 1

2

3

4

5

6

7

Rate of pollution abatement

1 2 3 4 5 7 10

0.649 0.649 0.649 0.649 0.649 0.649 0.649

0.715 0.748 0.645 0.762 0.653 0.718 0.73

0.774 0.816 0.646 0.828 0.666 0.778 0.812

0.797 0.846 0.64 0.862 0.669 0.801 0.848

0.823 0.858 0.64 0.891 0.676 0.827 0.882

0.823 0.859 0.633 0.907 0.678 0.828 0.9

0.829 0.86 0.633 0.918 0.677 0.834 0.911

Benefit of abatement

1 2 3 4 5 7 10

21.5 3658 32.8 −1151 317.6 1326 1394

23.76 3102.2 44.68 −1214 309 1506.9 4035

29.59 8785.6 58.407 −1280.05 293.614 2265.578 8161.57

43.575 4115.5 66.251 −1349.7 257.721 4154.411 30 173.21

48.015 14 486 71.871 −1423.12 242.112 5021.287 69 035.39

64.558 29 509 75.811 −1500.5 211.223 7625.489 60 324.68

82.282 20 870 80.565 −1582.07 204.04 11 458.57 150 265.9

Total cost of abatement

1 2 3 4 5 7 10

4.934 7.371 1.447 7.434 2.928 5.079 5.175

6.713 10.407 1.542 11.96 2.966 6.907 10.31

9.369 18.842 1.669 25.298 3.135 9.875 18.68

12.008 15.490 1.683 42.468 3.056 12.691 33.127

13.466 22.346 1.738 63.264 3.147 14.324 52.734

15.086 28.468 1.72 80.012 3.047 15.749 57.303

17.603 25.551 1.763 87.366 3.034 18.659 84.604

Total benefit of growth

1 2 3 4 5 7 10

4.948 39.135 −66.66 −1151 −1151 0.066 −547.1

1.117 −366.7 −48.97 −1214 −1214 −4.01 −579.5

−5.015 −149.168 −31.243 −1280.05 −1280.05 −7.643 −1279.94

46.031 14.418 −27.913 −1349.7 −1349.7 45.306 −1349.59

97.073 170.252 −30.199 −1423.12 −1423.12 98.743 −1423

138.977 199.656 −34.102 −1500.5 7.893 141.921 −1500.38

155.39 186.072 −37.65 −1582.07 0.774 160.545 −145.155

Total cost of growth

1 2 3 4 5 7 10

13.1 53.2 −109.6 54.17 −39.1 16 17.8

103.31 146.28 −77.09 155.93 34.8 105.45 143.25

153.66 203.458 −44.441 232.766 80.239 157.301 220.103

200.626 195.77 −14.672 306.705 108.55 204.512 291.848

237.792 263.286 12.164 376.925 134.705 242.792 362.528

288.016 350.748 34.636 434.472 151.519 290.882 396.639

343.818 386.457 55.878 475.71 170.38 349.019 472.346

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Table 8.3 Values of sustainability indicators Period Run 1

2

3

4

5

6

7

Environmental quality indicator

1 2 3 4 5 7 10

0.258 0.258 0.258 0.258 0.258 0.258 0.258

0.241 0.239 0.251 0.239 0.243 0.241 0.241

0.232 0.233 0.244 0.233 0.234 0.232 0.231

0.226 0.225 0.237 0.225 0.227 0.226 0.226

0.219 0.218 0.231 0.217 0.223 0.219 0.219

0.213 0.21 0.226 0.209 0.219 0.213 0.212

0.209 0.205 0.222 0.204 0.217 0.209 0.206

Ecological effect indicator

1 2 3 4 5 7 10

0.017 0.015 0.044 0.015 0.019 0.017 0.017

0.034 0.056 0.044 0.057 0.029 0.035 0.032

0.043 0.048 0.043 0.049 0.038 0.043 0.06

0.036 0.04 0.045 0.042 0.044 0.036 0.049

0.033 0.02 0.049 0.04 0.05 0.033 0.045

0.029 0.02 0.052 0.036 0.055 0.029 0.044

0.031 0.028 0.054 0.032 0.059 0.03 0.023

Indicator for resource supply demand

1 2 3 4 5 7 10

0.991 0.991 0.99 0.991 0.991 0.991 0.991

0.982 0.97 0.99 0.97 0.991 0.982 0.982

0.97 0.942 0.991 0.939 0.992 0.968 0.957

0.955 0.905 0.991 0.888 0.992 0.953 0.916

0.943 0.894 0.991 0.812 0.992 0.94 0.854

0.938 0.891 0.991 0.705 0.992 0.933 0.762

0.938 0.878 0.992 0.57 0.992 0.933 0.667

Unsustainability indicator: waste

1 2 3 4 5 7 10

0.066 0.057 0.174 0.057 0.076 0.066 0.065

0.144 0.242 0.175 0.245 0.122 0.148 0.134

0.19 0.219 0.178 0.224 0.162 0.19 0.273

0.168 0.196 0.193 0.211 0.196 0.168 0.239

0.161 0.101 0.214 0.227 0.225 0.159 0.244

0.146 0.109 0.231 0.243 0.252 0.145 0.274

0.159 0.154 0.247 0.274 0.272 0.156 0.166

Total damage from pollution

1 2 3 4 5 7 10

36.876 5384.2 1056.6 5430.1 2139 3709.9 3778

76.617 24 200.7 1911.9 26421 7360.3 15 348.1 22 056.9

113.777 44 451.4 3328.15 57231.5 15 004.7 30 610.8 55 248

162.315 44 858.95 5432.663 115 086.8 23 248.11 52 792.07 105 752.2

206.356 88 333.23 8248.986 213 628.7 33 020.71 84 040.18 193 808.3

289.543 243 839.9 11 573.63 335 917.7 41 555.4 144 603.2 252 066.1

421.007 426 256.5 15 577.45 444 448.7 51 643.17 273 324.9 429 809.7


251

1800 1600 1 2 3 4 5 7 10

1400 1200 1000 800 600 400 200 0 1

2

3

4 period

5

6

7

Figure 8.1. Socioeconomic variable: GDP. 700 600

1

500

2 3

400

4

300

5

200

7

100

10

0 1

2

3

4 period

5

6

7

Figure 8.2. Socioeconomic variable: consumption. 800 700 1 600

2 3

500

4

400

5 300

7 10

200 100 0 1

2

3

4 period

5

Figure 8.3. Socioeconomic variable: stock of pollution.

6

7

252

National and macroeconomic applications 800

1

700

2

600

3

500

4

400

5

300 200

7

100

10

0 1

2

3

4 period

5

6

7

Figure 8.4. Ecological variable: stock of non-renewable resources.

300

1

250

2

200

3 4

150

5 100

6

50

7 10

0 1

2

3

4

5

6

7

period

Figure 8.5. Ecological variables: waste from final and investment goods.

Model run 4 (output-maximization goal) has the greatest rise in per capita income over all periods. The second highest increase is in model run 10 (forecasting mode). Consumption results show a reverse pattern. Meanwhile, the savings level increases in model run 4. The zero discount rate causes initial consumption to be smaller, while the high initial saving and investment generate greater present and future GDP. More capital is available for future production, which lowers the rate of interest. The saving level varies from 0 to 60% in different model runs over the modelling period. The interest rate in model run 5 is lower over the entire time period than those under positive discount rate models. Optimal values of output, consumption, per capita consumption and output, investment and other economic variables fluctuate widely among model runs. The model determines optimal investment rates in different sectors. Values of ecological variables vary widely among model runs. Growth generates ever-increasing amounts of pollution. Model results show the unsustainability implied by the infeasible model solutions. They show growing


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unsustainability in the economy, falling environmental quality, stronger ecological impacts, rising resource shortages and higher levels of both waste and total pollution damage, over the planning period. These sustainability implications are derived from an utilitarian approach based on the social rate of discount. Other sustainability criteria, such as biodiversity preservation and resource conservation, could have also been included. Model run 7 (with a zero discount rate) generates relatively average sustainability indicators, but other model runs yield more positive sustainability indicators (see Table 8.3). Thus, other variables, parameters or policies also affect sustainability, besides the rate of discount.

8.4 Ecol-Opt-Growth-1 model conclusions The results of this model are similar to those of other models (Meadows et al., 1972; Van den Bergh, 1991, 1996). A positive trend, or even a constant level of economic performance, cannot be sustained in the long run, due to declining environmental quality. More optimistic, but cautious, conclusions are also generated by other models (Faber and Proops, 1990). More definitive conclusions require further empirical study (Meadows et al. 1972; Nordhaus, 2000). The major findings of this modelling study are that: (1) an ecologically sustainable economy cannot grow limitlessly; (2) economic growth is unstable and fluctuates; (3) optimal economic growth is fraught with difficulties such as infeasibility and non-sustainability. Thus, a long-run economic–ecological equilibrium does not appear to exist. Alternatively, optimal growth may not be durable. Further studies are needed to reconcile optimal and durable growth – see Section 2.3. In addition, (4) policy intervention is desirable to make development more sustainable, see Section 2.1.1 and (5) Ecol-Opt-Growth-1 does not show the key property, present in other multisector growth models, that investment in the relatively smaller (consumption goods) sector is initially lower relative to the bigger (capital goods) sector, but sectors grow uniformly after some period of time. The empirical results support growing concerns that the costs of economic growth may outweigh its benefits, resulting in unsustainability. Environmental costs and benefits have more impact on sustainability, although socioeconomic costs and benefits are also important. Basically, it has been determined that, in a wide range of circumstances, long-term economic growth is unsustainable due to increasing environmental costs. Nevertheless, the Ecol-Opt-Growth-1 model has many degrees of freedom and variables that can be explored by policy makers to make the development path more sustainable, as advocated by sustainomics. One example suggests that government-supported abatement programmes are needed to move toward sustainable development, since the model runs without abatement were infeasible. In most runs, the optimal rate of abatement increases over time. Therefore, pollution abatement is needed to improve ecosystem viability and make development more sustainable. The modelling experiments therefore confirm the view that optimal economic growth is not necessarily sustainable (Islam and Craven, 2003; Munasinghe et al., 2001). Further work is needed to seek specific conditions under which alternative growth paths are likely to be durable.

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8.5 Macroeconomic policies, second-best theory and environmental harm 8.5.1 Macroeconomic policies and general equilibrium theory Economy-wide policies (both macroeconomic and sectoral) often have much more powerful environmental and social effects than mere project-level investments (see Chapter 7). They need to be designed and implemented so that potential harm is anticipated and minimized, rather than reacting after the fact. Section 7.2.2 showed how imperfections (market, failures, policy distortions and institutional constraints) interact with economy-wide policies to cause environmental and social harm. Additional policies that complement (rather than hinder) macroeconomic policies may be used to correct such imperfections and avoid harmful impacts. We extend this approach to study the effects of macroeconomic policy failures. The idea here is that macroeconomic policies themselves may have unintended side effects (both positive and negative) on the environment. There are few consistent theoretical models available that analyse whether macroeconomic policies might be directly adjusted to avoid environmental or social damage. Thus, we develop a basic analytical framework to trace the environmental impacts of macroeconomic policies, to identify where negative effects may occur and to design remedial measures. Illustrative case studies are presented from selected developing countries. Mathematical details are provided in Appendix B, Section 8.8. 8.5.2 A simple case involving monetary policy and wage stickiness The first fundamental theorem of welfare economics states that, in an economy that is perfectly competitive and in which all goods and services are traded in markets, the resulting equilibrium is Pareto efficient – i.e. it is impossible to improve the welfare of anyone without impoverishing someone else. However, it is unclear if a competitive equilibrium exists, and whether the resulting income distribution among households is equitable. The second theorem of welfare economics addresses these two issues – if all goods and services are tradable, and if the economy is convex (production characterized by non-increasing returns to scale and to individual inputs, and consumption characterized by indifference curves, which are convex to the origin) and continuous (closed production possibility sets and ordinary consumer indifference curves), then any Pareto-efficient allocation of resources can be obtained as a competitive equilibrium after the initial endowments have been redistributed in a socially acceptable way. These idealized theorems provide a starting point for discussing the consequences of macroeconomic policies. The economy described by the theorems is really a barter economy. In the real world, we assume that money is introduced to pay for all transactions (Arrow and Hahn, 1971; Patinkin, 1965). Furthermore, we assume that the money supply is controlled by the government. Still, the government has no role in carrying out macroeconomic policies. Because all the markets function perfectly, the only thing that the government should do is to keep the money supply constant. (Even if the money supply changes, that would not matter, because all transactions are in real terms.)


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Let us now assume, however, that one central market does not operate smoothly enough – e.g. the labour market is characterized by sticky wages, due to union monopsonies or to insider–outsider relations or to any other realistic cause. The existence of sticky wages means that this single market in an otherwise perfect economy will not equilibrate automatically, and there may be unemployment or excess demand for labour with ensuing inflationary pressures. With sticky wages, macroeconomic policies now have a clear role. For example, if the initial situation is one with unemployment, an increase in money supply will tend to increase all monetary prices of goods and services outside the labour market, while nominal wages will remain unchanged – resulting in a fall in the real price of labour. If the increase in the money supply is adjusted until the real wage rate reaches the competitive equilibrium level, full employment will be restored. Conversely, decreasing the money supply will be the appropriate macroeconomic policy response if the economy is starting from a situation of excess demand for labour. Thus, in this simple model, a government can use monetary policies to maintain full employment by increasing or decreasing the money supply. Furthermore, this managed fullemployment equilibrium will correspond to a Pareto-efficient allocation. The monetary policy will be neutral vis-à-vis the allocation of resources (yielding the same outcome as in the case where the labour market equilibrates automatically). Let us now introduce another distortion in the economy, which affects the use of environmental resources. Consider a traditional externality where the government may allow plants to emit pollutants into the air without simultaneously compensating the victims of the ensuing air pollution. Such externalities are basically due to the absence of well defined property rights (Coase, 1960). This situation may arise for several reasons. First, it could be due to the inherent difficulty or impossibility of defining individual property rights. For example, because clean air in a town is shared by all inhabitants living there, it is impossible to define individual rights to clean air (which is now a public good). Second, the government may be unable to define property rights (e.g. tribal lands). Now, there are (at least) two deviations from full optimality or first-best allocation of resources – labour-market failure and resource failure. This is the classic second-best situation. Should we try to manage the money supply so that full employment is restored, assuming that we can do nothing about the environmental resource failure? According to the theory of second best, it is not socially optimal to equilibrate the labour market given the failure to allocate the environmental resource efficiently (Lancaster and Lipsey, 1956). Thus, a macroeconomic environmental policy failure occurs when macroeconomic policies aimed at correcting one allocation failure (labour market, unrelated to the environment) results, at most, in a second-best allocation because of a deterioration of the environmental resource base.

8.5.3 Effects of taxes Many macroeconomic policies can have environmental impacts, where the root of the problem is not directly connected to the environmental resource. When designing fiscal policies for macroeconomic stabilization, it is widely recognized that such policies carry

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deadweight burdens. An increase in taxes to reduce effective demand and generate government revenues generally creates distortions in the economy, especially in the case of taxes unrelated to real resource costs – such a tax increase cannot be implemented as a lump-sum tax. The conventional view is that the resulting deadweight burden is due mainly to distortions in the labour and capital markets. But taxes also affect the patterns of location and the structure of production, which in general also affect the environmental resource base. In this case, the root of the problem is that taxes have incentive effects, and an increase in taxes (to solve a macroeconomic problem) therefore has a deadweight burden that includes environmental deterioration. It is obvious that, in some cases, the deadweight burden will be negative. This would be the case when the environmental resources are underpriced and the tax increase takes the form of pricing these resources. Here there are three distortions: the general macroeconomic distortion, the distortion from tax increases and the lack of environmental pricing. With environmental taxes, the macroeconomic policy objectives can be achieved by taxes that improve the existing allocation of resources. This situation has given rise to the idea of a green-tax reform. Taxes on conventional factors of production (labour and capital) and taxes on commodities are distortive, whereas taxes on underpriced environmental resources improve the efficiency of resource allocation as well as provide tax revenues. Thus, it is thought that such a tax reform should have a double dividend (see Chapter 9). The first dividend would be the improvement in the environment, and the second would be the reduction of deadweight burden from existing taxes. However, some argue that a green tax may increase the excess burden from existing taxes with more than the corresponding reduction achieved by lowering these taxes (Bouvenberg and De Mooij, 1994). The same arguments obviously also apply to changes in expenditure patterns. Expenditures for ensuring increased effective demand will certainly have allocation effects. What are the effects of the increased government expenditures on environmental resource exploitation? They may be positive or negative, and it is necessary to take these effects into account when designing the fiscal and expenditure policies. The solution to these problems is to try to reduce the market failure that gives rise to the environmental degradation and thereby to improve on the second-best solution (see the Botswana and Ghana case studies below). Furthermore, because lump-sum taxes are not feasible, it follows that there will always be deadweight burdens. Ideally, the tax system should be designed to minimize the total deadweight burden (taking due account of distributional impacts). However, effects on the environment should then be included in measuring the deadweight burden. The mathematical model in Appendix B, Section 8.8, shows how this can be achieved in simple cases.

8.6 Developing country case studies Three brief examples from Botswana, Ghana and Morocco illustrate how macroeconomic polices and local distortions may harm the environment.


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8.6.1 Botswana Unemo (1996) studies how changing world-market prices might affect a domestic environmental asset like grazing land in Botswana. The main export commodity is diamonds, and the world-market price of diamonds chiefly determines the terms of trade of Botswana. On the face of it, a change in diamond prices should have no impact on grazing behaviour. However, based on general equilibrium effects, a change in the price of diamonds may have such an effect. Unemo uses a computable general equilibrium model to study the impact of an exogeneous change in the world-market price for diamonds. From a policy perspective, we could look at changes in export subsidies that would result in effectively the same change in terms of trade. A fall in diamond prices will increase overgrazing in Botswana and thus increase environmental costs. This is because a fall in terms of trade will reduce industrial profits and therefore the return on capital. Since capital is cheaper, investments in cattle will grow. Note that if there had been effective private property rights to land (or communal ownership with strict social control over the number of cattle that members of the community are allowed to graze) this would not be a problem. Each landowner would make a comparison of costs and benefits, taking into account the damage to grazing from increasing the herd. In fact, each cattle owner would bring as many cattle as possible to his grazing land up to the point where the selling price of the cattle would equal the marginal cost, including the environmental damage. Thus, he would balance the environmental damage with the increased profits from cattle herding. The change in terms of trade would not lead to macroeconomic policy failure. In large parts of Botswana, however, the grazing areas are under open-access common property regimes. In this case, each cattle owner would bring as many cattle to the commons as is profitable to him. Because he does not consider the damage he is inflicting on others, he will continue to add cattle to the point where price equals average cost. The average cost curve is less steep than the marginal cost curve, and the result is therefore a bigger increase in the number of cattle brought to the grazing land than would take place with private property rights. Here we would have a macroeconomic policy failure. It is important to note that the lack of private property rights is basically responsible for this failure, rather than the original fall in diamond prices (or reduction in export subsidies).

8.6.2 Ghana The role of institutional constraints in macroeconomic reforms is examined in (López, 1993). Here, trade liberalization reduces taxes on agricultural exports and leads to increased production incentives, while efforts to reduce the government wage bill increase unemployment. Thus, the adjustment process helps to stimulate production of export crops and combines with rapid population growth and lack of employment opportunities outside the rural sector to create increasing pressure on land resources, encroachment onto marginal lands and soil erosion. This effect on resource use is influenced by the allocation of property

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rights. Whether in relation to the security of land tenure of peasant farmers or to the right to extract timber of logging companies, uncertainty normally results in environmental degradation. In Ghana, as in many regions in Africa, agricultural lands are governed by traditional-land-use institutions, and farms are communally owned by the village or tribe. These common-property regimes may have been sufficient to ensure sustainable use of agricultural lands when populations were much smaller and fallow periods were long enough to allow land to regain fertility. However, such traditional arrangements have been overwhelmed by economy-wide forces, resulting in reduced fallowing, loss of soil fertility and environmental decline. The best remedy would be to revise the land-tenure regime to resist externally induced pressures. This study analyses the effects of ongoing trade liberalization and public employment reduction on agricultural productivity and land use in the country’s western region. A noteworthy outcome of the policy simulations is that the main source of supply response is the expansion of cultivated area rather than agricultural intensification. Biomass (proportion of land under forest cover) is an important factor of production, contributing 15–20% of the value of agricultural output. This compares with contributions from ‘conventional’ factor inputs: 26% for land cultivated, 25% for labour and 26% for capital. Because the share of agricultural output in GDP is about 50%, the contribution of biomass to national income is about 7.5%. Thus the stock of biomass is an important determinant, not only of agricultural production, but also of GDP. A large proportion of the land is currently reserved exclusively for the use of villagers. The system is consistent with shifting cultivation because the individual has exclusive rights to the cultivated land, but, once the land is left fallow, it can be reallocated by village consensus. Under these conditions, biomass is already being overexploited. Fallow periods are too short, and the environmental resource stock is below socially optimum levels. The study finds that increasing agricultural prices or reducing wages causes an expansion in the cultivated area and raises output. For example, a 10% increase in land cultivated leads to a 2.7% increase in the direct output effect. However, such an increase in cultivated area leads to a reduction in fallowing, and total biomass declines 14.5%. This, in turn, leads to a 2.5% loss of sustainable agricultural productivity. Thus, the net effect of expanding the area cultivated (2.7% direct output effect less 2.5% biomass loss effect) is a mere 0.2% – many times smaller than the direct effect alone. In addition to policy changes, other factors contribute to expansion of cultivated area: large family size, availability of capital and the presence of migrant populations in the area. The results suggest that, in general, economy-wide price and wage policy reforms that do not include changes in land management practices will have very limited impact on national income, once the existence of land quality effects is considered. For example, the effects of further reducing implicit taxation of agriculture are, in general, ambiguous, while the effects of import liberalization are perverse. However, reducing the fiscal deficit (through reducing public employment or wages) has unambiguously positive effects on agriculture and national income.


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If agricultural price responsiveness relies less on land expansion and more on intensification, trade liberalization would be a better outcome. Without institutional reforms and with land still available for cultivation, the main supply response will continue to be based on agricultural expansion. Indeed, in the study area (the western part of Ghana), the economy-wide policy reforms lead to an expansion of cultivated area and thus a decline in fallowing. Environmental and socioeconomic data indicate that fallowing (measured as the ratio of forest biomass to cultivated land) contributes as much to agricultural production as other more conventional inputs, such as the area cultivated, labour or capital. Less fallowing reduces the positive effect of the reform on agricultural output. Thus, complementary institutional reforms will be needed to ensure that the current gains from adjustment reforms will be sustainable.

8.6.3 Morocco The Morocco study focuses on how links between macroeconomic policies and existing water allocation system have led to sub-optimal and unsustainable patterns of water use (Goldin and Roland-Host, 1997). Specifically, low water charges (coupled with ineffective collection of these charges) have artificially promoted production of water-intensive crops such as sugar cane. Rural irrigation water accounts for 92% of the country’s marketed water use. At the same time, irrigation charges cover less than 10% of the long-run marginal cost, and the corresponding figure for urban water tariffs is less than 50%. Thus, a water deficit is projected for Morocco by the year 2020, despite high water-sector investments. Going beyond the traditional sectoral remedy of raising water tariffs, the study links sectoral policy reforms with ongoing macroeconomic adjustment policies (removal of nominal trade tariffs). As a consequence of the trade reforms, prices of sugar, cereals, oilseeds, meat and dairy products would decline to world levels from their current protected levels. Further, a simultaneous introduction of trade and water pricing reforms would imply increased input prices and reduced output prices. A computable general equilibrium model traces the impact of these reforms on output, consumption, imports, exports and the use of factors of production (including water) by the different sectors in the economy. To separate out the effects of sectoral and macroeconomic reforms, the study considers three scenarios: trade reform only, water pricing reform only and a combination of the two. In the first scenario, the only policy change is a complete removal of nominal tariffs (which in 1985 averaged 21% for the whole economy and 32% for agriculture). In the second scenario, the sole change is that the price of rural irrigation water is doubled. In the final scenario, the two policy reforms are combined. In the first scenario, liberalization of trade alone has positive effects – a small rise in real GDP, large gains in incomes and consumption as import barriers are reduced, more competitive exports, greater domestic purchasing power and more efficient resource allocation. However, two major drawbacks are that elimination of tariffs leads to

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budgetary deficits and domestic water use rises sharply due to growth – resulting in increased environmental pressures. In the second scenario, reforming water prices alone reduces water use by 34% in rural areas and by 29% for the whole economy. This static efficiency gain also causes real GDP to fall by about 0.65%, while incomes and real consumption of both rural and urban households decline by approximately 1%. In the final scenario, the growth in real GDP due to trade liberalization remains, but reforming water prices still induces substantial reductions in overall water use. Thus, the combination of trade reforms and improved water pricing provides both economic and environmental gains. 8.6.4 Concluding thoughts The model confirms the empirically observed and intuitive conclusion that macroeconomic policies may combine with subsidiary imperfections to cause environmental harm. Many economic imperfections may remain unnoticed in a stagnant economy, if the resultant environmental damage is minor. However, once economic growth is induced by macroeconomic reforms, the environmental harm will rapidly worsen, and the underlying imperfections can no longer be ignored. The first-best remedy would be to eliminate the subsidiary imperfections without changing macroeconomic policies. If real-world constraints delay such corrective action, then a second-best situation arises. Then, there is justification for modifying, or fine-tuning, macroeconomic policies to reduce harm. Relevant policies could be progressively intensified over a period of time, as the subsidiary imperfections are gradually eliminated by other means. Because the impacts of macroeconomic policies on the environment work through complex and indirect mechanisms, a general equilibrium analysis will provide useful insights. 8.7 Appendix A: The Ecol-Opt-Growth-1 model All symbols used in the following equations are explained in the following sections. Objective function: X Obj ¼ ð1 þ Þt OðPopðtÞ; cðtÞ; KðTÞÞ: t Definition of the per capita consumption: cðtÞ CðtÞ=PopðtÞ: Definition of GDP: Y ¼ YðQðtÞ; IðtÞ; tÞ; Y ¼ Y2 ðKðtÞ; LðtÞ; TrdðtÞ; Rsup ðtÞ; EðtÞ; WQ;I ðtÞ; tÞ:

8 Mathematical macromodel applications Output: Q ¼ QðKQ ðtÞ; EðtÞ; Rs ðtÞ; Trd ðtÞÞ: Capital accumulation in the final-goods sector: KQ0 ðtÞ ¼ F1 ðKQ ðtÞ; IQ ðtÞ; tÞ: Aggregation of sectoral capital: KðtÞ ¼

X

Kj ðtÞ:

j2K

Aggregation of sectoral investment: IðtÞ ¼

X

Ij ðtÞ:

j2K

Distribution of final goods: CðtÞ þ Ord ðtÞ ¼ QðtÞ: Final-goods-sector investment: IQ ¼ IQ ðKQ ðtÞ; KðtÞ; IQ ðtÞ; tÞ: Other sector investment: Ii ¼ Ii ðKQ ðtÞ; Kj ðtÞ; IQ ðtÞ; Ij ðtÞ; tÞ;

j 2 J:

Sectoral capital equations: Kj0 ðtÞ ¼ F2 ðKj ðtÞ; Ij ðtÞ; Kj ðtÞ; tÞ;

j 2 J:

Technological growth rate equation: 0 Trd ðtÞ ¼ F3 ðTrd ðtÞ; ee ðtÞ; Ord ðtÞ; QðtÞ; IðtÞ; tÞ:

Population growth rate: Pop0 ðtÞ ¼ F4 ðPopðtÞ; CðtÞ; tÞ: Waste abatement: Rwa ¼ Rwa ðKwa ðtÞ; Trd ðtÞ; WQ;I ðtÞ; tÞ: Recycled resource rate: Rrec ¼ Rrec ðTrd ðtÞ; Krec ðtÞ; Wrec ðtÞ; tÞ: Renewable resource extraction rate: Rn ¼ Rn ðKn ðtÞ; NðtÞ; EðtÞ; tÞ: Non-renewable resource extraction rate: Rs ¼ Rs ðKs ðtÞ; SðtÞ; tÞ:

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Change in the stock of stored waste: S0wa ðtÞ ¼ F5 ðSwa ðtÞ; Rwa ðtÞ; Wrec ðtÞ; Rrec ðtÞ; tÞ: Change in the total supply of resources: R0sup ðtÞ ¼ F6 ðRsup ðtÞ; RN ðtÞ; Rs ðtÞ; Rrec ðtÞ; Trd ðtÞ; QðtÞ; tÞ: Gross waste from final-goods and investments sectors: WQ;I ¼ WQ;I ðQðtÞ; IðtÞ; Trd ðtÞ; tÞ: Waste amenable for recycling: Wrec ¼ Wrec ðQðtÞ; KQ ðtÞ; KðtÞ; Rwa ðtÞ; tÞ: Waste emitted: Wem ¼ Wem ðWQ;I ðtÞ; Rwa ðtÞ; Wrec ðtÞ; Rrec ðtÞ; tÞ: Required extraction rate of resources: Rnew ¼ Rnew ðKQ ðtÞ; EðtÞ; Trd ðtÞ; Krec ðtÞ; tÞ: Ecological effect indicator: E ¼ EðNðtÞ; BðtÞ; PðtÞ; tÞ: Change in stock of renewable resource: N 0 ðtÞ ¼ F7 ðNðtÞ; EðtÞ; RN ðtÞ; tÞ: Pollution accumulation: P0 ðtÞ ¼ F8 ðPðtÞ; EðtÞ; Wem ðtÞ; tÞ: Change in stock of slowly renewing resource: B0 ðtÞ ¼ F9 ðBðtÞ; EðtÞ; IðtÞ; KQ ðtÞ; CðtÞ; PopðtÞ; Rn ðtÞ; Rs ðtÞ; KðtÞ; BðtÞ; tÞ: Change in stock of non-renewable resources: S0 ðtÞ ¼ F10 ðSðtÞ; Rs ðtÞ; tÞ: Material balance condition: GðN; EÞ ¼ MðP; EÞ: Total damage: dm ¼ dmðYðtÞ; 1 ðtÞ; PðtÞ; tÞ: Damage avoided by control: dv ¼ dvðYðtÞ; 1 ðtÞ; Rwa ðtÞ; tÞ:

8 Mathematical macromodel applications Abatement rate: ar ¼ arðRwa ðtÞ; WQ;I ðtÞ; tÞ: Abatement cost: ac ¼ acðYðtÞ; arðtÞ; tÞ: Savings rate: s ¼ sðIðtÞ; YðtÞ; tÞ: Capital output ratio: k ¼ kðKðtÞ; YðtÞ; tÞ: Capital labour ratio: kp ¼ kpðKðtÞ; PopðtÞ; tÞ:

8.7.1 Model notation Stock variables B K KI Kn KQ Krec Ks Kwa N P Pop Rsup S Swa Trd Z

= slowly renewable resource (soil, land, water) = total economic capital = investment-sector capital = renewable-resource-extraction capital = productive sector = recycling capital = non-renewable-resource-extraction capital = waste-abatement/treatment capital = stock of renewable resources = stock of pollution in natural mediums or organisms = human population level = total supply of natural-resource materials in inventory = stock of non-renewable resources = stock of useless, stored waste = progress indicator of environmental technology = artificial variable (total ‘real’ output delayed) Flow variables

C ee E I Ii (i 2 K) Kocc LD

= consumption = ecological effect indicator for technical progress = indicator for overall environmental quality = total investment in replacement and new capital = investment in sector i = used economic capital = employment (jobs)

263

264 LS Ord Q Rdem Rn Rs Rwa U Wem WQ,I Wrec Wtoo


= labour force = social investment in research and development = output of final-goods sector = total productive and consumptive demand for resources = renewable resource extraction = non-renewable resource extraction = abated/treated waste = long-term labour-market unbalance (unemployment) = emitted waste = gross waste from final- and investment-goods sectors = waste amenable for recycling = indicator for unsustainability of waste emission Functions

A B bi (i = 1,…,5) cQ cI Di(i∈K) frec fwa Fi−1(i = 1,…,6) FI FN FQ FS G H α ε dm(t) dv(t) ar(t) ac(t) s(t) k(t) kp(t) M(P, E) G(N, E)

= assimilation function = population growth rate = regeneration and damage functions of slowly renewable resources = ratio of resource input to material output in final-goods sector = ratio of resource input to material output in investment-goods sector = discarded capital = part of waste amenable for recycling that is recycled = part of production waste that is abated/treated = determine for each sector used capital = unrestricted production function in investment-goods sector = unrestricted production function in renewable-resource-extraction sector = unrestricted production function in final-goods sector = unrestricted production function in non-renewable-resource-extraction sector = regeneration function of renewable-resource capacity = environmental quality function = general investment effect parameter on technology = effect of social R & D investment and part of production increase on technology = total damage = damage avoided by control = abatement rate = abatement cost = savings rate = capital output ratio = capital labour ratio = waste assimilation = regeneration function

Table 8.4 shows the parameter values used in Ecol-Opt-Growth-1. The boundary conditions on the state and control variables applied are shown in Table 8.5. The initial and the terminal values of the variables are also adopted from Van den Bergh (1991).


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Table 8.4 Values of parameters 1 a aB aP APop Arec Awa bi bcrit Bwa Cn Cwa d " Ecrit

1 Pcrit Ncrit r s1 s2 ki pN pS 2 1 b1 b2 1 1

0.1 0.098 500 0.5 5 0.8 0.95 550 100 18 30 000 1.2 1 0.025 0.096 0.8 0.1

0.1 450 15 000 0.05 0.03 0.5 0.5 1 1 1 100 2 0.001 44 0.0686 2.887 0.3 0.5

Table 8.5 Initial conditions KQ ð0Þ ¼ 43 Krec ð0Þ ¼ 5 Popð0Þ ¼ 100 Nð0Þ ¼ 100 00 Zð0Þ ¼ Qð0Þ þ Ið0Þ

Ki ð0Þ ¼ 3:6 KN ð0Þ ¼ 30 Trd ð0Þ ¼ 100 Sð0Þ ¼ 3000

Kwa ð0Þ ¼ 5 KS ð0Þ ¼ 30 Rsup ð0Þ ¼ 300 Pð0Þ ¼ 100

8.8 Appendix B: Second-best nature of macroeconomic policies when environmental externalities are present This simple model assumes that individuals value real balances for various reasons (mainly to reduce transaction costs) and that the demand for such balances is determined by prices, wealth and initial balance (Patinkin, 1965). Furthermore, it is a disequilibrium model with sticky wages. A typical consumer has the following utility function: M U ¼ U x; E; Ls ; ; (8:1) p where x is demand for the consumption goods, E is a vector of emissions of pollutants to the environment, Ls is the desired supply of labour, M is the demanded nominal money balance

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and p is the price for the consumption goods. Thus, 1/p is the price of money. The inclusion of money in the utility functions has been severely criticized (Arrow and Hahn, 1971). The budget constraint for the representative consumer can be written as px þ M þ T ¼ wLd þ M0 ;

(8:2)

where w is the wage rate, Ld is the demand for labour (which, in the case of wage stickiness, may be different from the desired supply) and T is the lump-sum tax paid by the consumer. With a fixed wage rate, the demand for labour, Ld, must be smaller or equal to the supply of labour, Ls. Utility maximization subject to the budget and labour supply constraints yields the net demand functions for goods and money: x ¼ xd ðp; E; M0 ; wÞ; M ¼ M d ðp; E; M0 ; wÞ:

(8:3)

For the supply of goods and services, we assume that the production function has constant returns to scale and has the following form: x ¼ f ðLd ; EÞ:

(8:4)

Note that emission of pollutants is regarded as a factor of production. Let us assume that the government is internalizing the emissions by charging firms with q per tonne emitted. The profit is then given by p ¼ pf ðLd ; EÞ wLd qE:

(8:5)

Maximizing profits yields the following demand and supply functions: x ¼ xðp; w; qÞ; Ld ¼ Ld ðp; w; qÞ;

(8:6)

E ¼ Eðp; w; qÞ: Let us now consider the public sector. The government is responsible for taxing individuals, controlling the money supply and controlling the emissions to the environment. The budget in the public sector is given by T þ M þ qE ¼ 0:

(8:7)

If the government has determined the marginal willingness-to-pay for environmental improvements and set the emissions charge equal to this marginal willingness-to-pay, then q ¼ p

@U=@E ¼ ðp; E; M0 ; wÞ: @U=@x

(8:8)


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Here, gives the marginal willingness-to-pay for the public good as a function of the variables determining the budget constraint for the individual. By this assumption, we are assured that there will always be an optimal level of pollution. Assume for the moment that wages are flexible so that the labour market clears. Then it follows from the model that money is neutral and a change in the money supply has no real consequences. Furthermore, the resulting allocation of resources is efficient. However, the point to be made has to do with sticky wages. Assume that the wage rate is exogenously given by w ¼ w:

(8:9)

is high enough, the total demand for labour is less than the exogenously given supply Ls, If w and there is unemployment. Now there is room for government macroeconomic policies. An increase in the money supply now affects the real economy. The mechanism is the conventional one. After an increase in the money supply, each individual finds himself with real balances that are too high, which increases the net demand for goods and services. This increases the prices of goods and services in general and thereby reduces the real money balance held by individuals and increases the output and therefore the demand for labour. Thus, the real wage rate falls, and it is possible to reach full employment. However, in the process, the emissions have probably increased, and the environment has therefore probably deteriorated. This is as it should be, because the polluters are paying the marginal social cost of pollution. The gains from increasing the employment exceed the loss in environmental quality. If the marginal social cost of pollution rises very sharply with increases in pollution, the end result comprises only marginal increases in emissions and the monetary expansion causes reallocations between different sectors so that less polluting sectors expand and more polluting sectors contract. In the end, full employment is generally reached. Obviously, if the marginal willingness-to-pay for environmental quality is inelastic with respect to emissions, and if the emissions per tonne of output are very high, there may not exist a full employment equilibrium. However, we will disregard that possibility because plants always have ways of abating emissions other than reducing production. In order to study this closer, let us depart from the assumption that the emission charge is optimal. On the contrary, assume that q is less than the marginal willingness-to-pay for pollution abatement. In such a situation, what is the effect of an increase in money supply? Differentiating the utility function yields the following: dU ¼ Ux dx þ UE dE þ UL dL þ UM dðM=PÞ ¼ pdx qdE þ ws dL þ YdðM=PÞ ¼ ð w ws ÞdL ðq q ÞdE þ YdðM=PÞ:

(8:10)

The first parenthesis in the final line indicates that an increase in the demand for labour increases welfare as the fixed wage rate exceeds the reservation wage, ws. The second parenthesis indicates, however, that the increase in pollution reduces well-being as the

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marginal willingness-to-pay exceeds the emission charge. If the emission charge were equal to the marginal willingness-to-pay, then it would obviously have been optimal to increase the money supply until the reservation wage rate equals the fixed wage rate. However, in the face of a less than optimal pollution charge, this is not optimal. In fact, equation (8.10) says that the increase in money supply should be smaller than what would correspond to full employment. Thus, if it is not possible to optimize the allocation rule regarding the environment, it is not optimal to try to achieve optimal macroeconomic policies.

9 Computable general equilibrium modelling applications1

In this chapter, two case studies demonstrate the use of computable general equilibrium (CGE) models to analyse economy-wide sustainable development issues and explore economic–social–environmental links. Sections 9.1 to 9.4 develop the ECOGEM model to assess economic, social and environmental policy linkages in Chile – focusing on urban air pollution, poverty, income distribution and employment. The model examines the potential for combining different policies to enhance positive cross-effects of environmental and social policies, or to mitigate the negative side-effects of any single policy. The results show that general equilibrium modelling is useful for holistically analysing the impacts of different economy-wide policies. Winners and losers may be identified with the potential magnitude of gains and losses, including indirect effects. In Sections 9.5 to 9.7, a static CGE model of Costa Rica is used to study the effects of macroeconomic policies on deforestation and to identify remedial policy options. The model confirms the results of partial equilibrium analyses: (1) establishing property rights tends to decrease deforestation, because such rights allow forest users to capture the future benefits of reduced logging damage today and (2) higher interest rates promote deforestation and vice versa. The CGE approach also clearly identifies the indirect effects (due to intersectoral links), which must be combined with the direct effects to determine the total impact. Finally, the model underlines the importance of pursuing sectoral reforms in the context of growth. A dynamic CGE model of Costa Rica gives essentially the same results as the static CGE model presented here.

9.1 Economy-wide cross-effects of social and environmental policies in Chile Sustainomics encourages a wider view of human well-being that looks beyond traditional economic goals and pays more attention to social and environmental effects. Below, we analyse the links among social and environmental policies and their cross-effects as well as the impacts on key macroeconomic and sectoral variables, within a general equilibrium 1

The valuable contributions of C. de Miguel, S. Miller, A. Persson and R. O’Ryan to this chapter are gratefully acknowledged. Some parts of the chapter are based on material adapted from Munasinghe (1996a), Munasinghe et al. (2006) and Persson and Munasinghe (1995).

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270


macroeconomic modelling framework applied to Chile. This work extends recent research on the powerful and pervasive impacts of country-wide or economy-wide policies on environmental and social issues (Munasinghe, 2002b). In Section 9.1, we summarize the CGE modelling framework that is used, and then we review the relevant literature. Section 9.2 describes the main economic, social and environmental issues and policies in Chile. The ECOGEM–Chile model is applied to simulate alternative environmental and social policies, and the results are discussed in Section 9.3. Finally, Section 9.4 summarizes the main conclusions.

9.1.1 CGE approach General equilibrium models capture complex interlinkages among economic, social and environmental variables better than partial equilibrium methods. It is often difficult to integrate these three major domains (see Chapter 2). Given the complexity of direct and indirect links among economic, environmental and social variables, CGE models represent the economy of a country in a more realistic way by incorporating market mechanisms in resource allocation. They are useful in defining the main linkages and in evaluating quantitatively ex ante the effects of different economic, social or environmental policies, while capturing indirect side-effects. Our study focuses on changes in selected economic, environmental and social variables. Figure 9.1 summarizes the relationships to be modelled by the CGE model, based on the circular flow of the economy. It includes the main agents (firms, households and government), flows of goods and services, payments to factors, international trade and relationships with the environment. Each agent is modelled according to certain behavioural assumptions,

rest of the world exports goods and services consumption natural resources

emissions

household income distribution

capital and assets

government

firms

natural resources

emissions

skilled and non-skilled labour

imports

labour and capital wages and rents

industrial interrelations

ecosystem

Figure 9.1. Circular flow in the economy. Source: Munasinghe et al. (2006).

9 CGE modelling applications

271

including optimizing producers and consumers. Further, each market reflects economic reality, as a competitive or non-competitive market, or, in the case of the labour market, with or without full employment. These models reach equilibria according to Walras law, by equating demand and supply and thus determining prices and quantities. The productive sectors incorporate demands for intermediate inputs as well as capital and labour. However, they go beyond simple input–output models by allowing substitution among production inputs. This characteristic yields equilibria which capture transmission of effects through all relevant markets. Additionally, the government role is modelled via taxes, subsidies and transfers. Finally, the CGE model integrates the analysis of short- and long-run development strategies and growth paths, with the short-run view focusing on stabilization policies. Sectoral analysis is related to technological or investment processes. Models for developing countries have become more practical by moving away from the original, strictly neoclassical, general equilibrium approach. Typical adaptations include departures from the Walrasian orthodoxy to account for structural rigidities such as fixed wages, absence of factor mobility (Taylor, 1990) and imperfect competition and increasing returns to scale in trade models.

9.1.2 Linkages with the environment Chapter 7 reviewed the environmental and social impacts of economy-wide policies, some of which have emerged from CGE models applied to developing countries (De Miguel and Miller, 1998; Dessus and Bussolo, 1996; Munasinghe, 1996b; Munasinghe and Cruz, 1994; Persson and Munasinghe, 1995; Rodríguez, Abler and Shortle, 1997). More generally, since the first environmental CGE models appeared (Dufournaud, Harrington and Rogers, 1988; Forsund and Strom, 1988), the recent literature includes: (1) models to evaluate the effects of trade policies or international trade agreements on the environment (Beghin et al., 1996, 2002; Grossman and Krueger, 1993; Lucas, Wheeler and Hettige, 1992; Madrid-Aris, 1998; Yang, 2001) or diverse applications in the area of the Global Trade Analysis Program (Hertel, 1997); (2) models to evaluate climate change, focusing on the stabilization of CO2, NOx and SOx emissions (Bergman, 1991; Edwards and Hutton, 2001; Jorgensen and Wilcoxon, 1993; Li and Rose, 1995; Rose and Abler, 1998); (3) models focused on energy issues, which evaluate the impacts of energy price changes on pollution or costs control (Pigott, Whalley and Wigle, 1992; Rose, Schluter and Wiese, 1995); (4) natural-resource allocation or management models, whose goal is usually the efficient interregional or intersectoral allocation of natural resources such as water among competing uses (Ianchovichina, Darwin and Shoemaker, 2001; Mukherjee, 1996; Robinson and Gelhar, 1995); and (5) models focused on evaluating economic impacts of specific environmental instruments or regulations, like the Clean Air Bill in the USA (Hazilla and Kopp, 1990; Jorgensen and Wilcoxon, 1990). Finally, CGE models have focused recently on double dividend issues – i.e. the hypothesis that shifting from (distortionary) ordinary taxes to pollution taxes will improve both economic and environmental welfare (Auerbach, 1985; Repetto et al., 1992). CGE models have been used to argue both in favour of and against the existence of a double dividend (see, e.g., Bento

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and Rajkumar (1998), Bovenberg and De Mooij (1994), Fullerton and Metcalf (1997), Jaeger (2001), Koskela, Schöb and Sinn (1999) and Parry and Bento (1999)). Van Heerden et al. (2006) shows a triple dividend (lower GHG emissions and poverty and higher GDP) when environmental taxes are recycled through reduced food prices in South Africa.

9.1.3 Applications in Chile There are few applications of CGE models to Chile. Early attempts sought to analyse the economic effects of alternative tax policies and trade agreements between Chile and MERCOSUR, NAFTA, the European Union, the USA and Asia-Pacific (Coeymans and Larraín, 1994; Harrison, Rutherford and Tarr, 1997, 2002; Ruiz and Yarur, 1990). Bussolo, Mizala and Romaguera (1998) analysed the effects of trade agreements on the labour market, under competitive conditions and with some rigidities. Holland et al. (2002) studied the impacts of agricultural reforms consisting of price-band removal and elimination of tariffs on agricultural and food commodities in Chile, in relation to urban employment, rural–urban migration and welfare. Environmental issues were addressed in the dynamic CGE model of Beghin et al. (1996) – based on the OECD TEQUILA model. This study analysed the impact of environmental policy, trade liberalization and trade agreements, using a multiregional model that included 26 regions and 72 productive sectors. It determined the emissions from productive activity at the national level, scaled for Santiago. The air concentration of particulates is estimated for Santiago by using a linear dispersion model for air pollutants. A dose–response function translates this concentration into indices of mortality and morbidity. The abatement of particulate matter, SO2 and NO2 will reduce mortality and morbidity significantly. Meanwhile, the entry of Chile into NAFTA would be beneficial for the environment, whereas the entry into MERCOSUR or a unilateral drop in tariffs will not. Taxing these pollutants leads to increased emissions and concentrations of substitutes which are also toxic, as well as bio-accumulative gases, thereby decreasing mortality and morbidity. Beghin and Dessus2 (1999) applied a static version of the same model to assess the issue of double dividend, by substituting trade distortions for environmental taxes. O’Ryan, Miller and De Miguel (2003) applied an adaptation of the OECD model to evaluate policy options for reducing air pollution in Chile. The preceding examples use CGE models to assess economic and environmental linkages. However, no one has evaluated the cross-links between the social and the environmental spheres of sustainable development. Section 9.3 addresses this issue.

9.2 Review of economic, social and environmental issues and policies Since the mid 1980s and up to the end of the twentieth century, Chile was a role model for developing countries due to its rapid export-led growth. Further, there were major reductions 2

Mimeograph by J. Beghin and S. Dessus (1999), ‘The environmental double dividend with trade distortions. Analytical results and evidence from Chile’.


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in poverty during that period, but the environment suffered severe harm. This section discusses the main economic, social and environmental issues and policies introduced to reduce such pressures after the mid 1990s

9.2.1 Economic issues and policies During the 1980s, Chile engaged in trade liberalization and extensive privatization programmes, promoting exports and free markets as the main engines for growth. This trend continued in the 1990s, but less strongly. The government did not set prices, except for public transport, some public utilities and port charges. Tariffs applied to countries without free-trade agreements are uniform, and currently at 6%. Regulation of utilities, banking, security markets and pension funds was improved. At the same time, major efforts were made to maintain macroeconomic stability, improve infrastructure provision and focus resources to address social problems. Key reforms implemented include: privatization of public utilities; promotion of private investment in infrastructure, electricity, telecommunications and air transport; trade liberalization and trade agreement expansion; and educational reform. Legislation is now in place to privatize ports, water and sewage. In the future, a system of licenses is expected to replace direct privatization. As a result, Chile’s economic performance during the 1990s was the best of the twentieth century, growing at an impressive 8% per year between 1989 and 1998. The 1997/98 Asian Crisis caused a small recession in 1999. Despite adverse international events, the economic growth rate in 2000 remained at 4.5%, decreased to 3.4% in 2001, and rebounded to 5% by 2004. Chilean economic performance far exceeded that of other countries in the region (where growth rates are a poor 0 to 1%). Per capita GDP is around US $4.5 at current prices. Key variables have been kept within acceptable limits. Since the beginning of the 1990s, the Central Bank has posted an inflation target for the year, resulting in a fall in inflation from 27% in 1990 to 2.8% in 2002. Tight government spending helped to achieve fiscal surpluses each year up to 1999. Fiscal expansion has been moderated and the deficit easily balanced. The current account was in deficit during most of the 1990s (currently under 1% of GDP), but has been easily financed by substantial foreign capital inflows. External debt composition changed from 30% private debt in 1990 to 85% in 2002, and comprises mainly medium- and long-term debt (83%). External debt (US $39 million) accounts for 58% of GDP. Gross internal investment has increased significantly in the period, reaching 27% of GDP in 1998, compared with the 16% average of the 1980s. However, internal savings did not grow much during the 1990s, and most of the increase in investment has been financed through foreign savings. After 1998, investment slowed to 23% of the GDP, with a parallel reduction in foreign savings. Real wages increased in the 1990s at an average rate of 3.2%. Unemployment fell from an average of 18% in the 1980s to 6% in the 1990s. However, after 1999 unemployment rose to 10%, and, despite efforts by the government, this remains at 9%. Poverty declined sharply from 45% of total households in 1987 to 22% in 1998 and further to 20.6% in 2000. Income distribution is still a weak area. The minimum wage, although increasing at a higher real rate

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than wages, was only US $160 per month in 2002 (or about twice the value defined by the poverty line). The richest 20% of homes received more than 15.5 times the income of the poorest 20% in 2000; the Gini coefficient was close to 0.58. This situation has not changed since the 1960s. Historically, Chile’s growth has been based on renewable and non-renewable resources. Chile is the world’s leading copper and iodine producer and is a growing source of gold, lithium and other non-metallic minerals. Copper is the main export product, equivalent to around 40% of its total exports – down from 80% in the 1980s, due to diversification of exports. Agricultural products, fish and fishmeal, forestry products and cellulose are other important export sectors that have grown rapidly since the mid 1990s. Imports are concentrated in capital goods and fuel/energy.

9.2.2 Social issues and policies Since 1990, public expenditure on social issues has increased greatly in an attempt to reduce high levels of poverty. Following the basic principle of equal opportunities and an acceptable standard of living for the population, social policy since the mid 1990s has been geared to improving coverage in the health, education and housing sectors. In addition, efforts have been made to promote productive development in poor areas. Three distinct periods can be identified in the evolution of social policies in Chile (Baytelman et al., 1999; Schkolnik and Bonnefoy, 1994). During the first period (1950– 1973), termed ‘Universal Policies’, there was a gradual growth in public social expenditure, coverage and number of beneficiaries. Programmes were designed to have universal coverage, and were basically aimed at health and nutrition, education, housing and sanitary infrastructure. However, these programmes were usually underfinanced and caused severe fiscal deficits. The second period (1973–1989), called ‘Assistance and Subsidies’, was undertaken (by the military government) amidst intense economic and political reforms. Public-sector services were decentralized and the private sector was encouraged to deliver social services. Broad programmes were reduced and expenditure focused on specific objectives. The main goal was to eradicate extreme poverty and to provide mother–child care and basic services. Social expenditure was severely reduced. Nevertheless, there were significant improvements in human development indicators, such as child mortality, reduction of illiteracy and schooling, among others. The third period, ‘Integrating Policies’, was begun by the democratic government in the 1990s. Spending on social goals increased greatly. Social policies are focused on improving the quality of services, and aim to develop skills in the low-income population. Social investment is preferred over assistance. This view reflects the new government goals of economic growth and macroeconomic stability together with equality and poverty reduction (and not just as a consequence of growth). Between 1990 and 1998, public social expenditure grew by 88% (66% in per capita terms), an annual growth rate of 8.2%. This increase was much higher than the regional average for Latin America (5.5%) (CEPAL, 1999, 2000). Thus,


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Table 9.1 Government social expenditures 1990–2002 1990

1992

1994

1996

1998

2000

2002

Social expenditures (% GDP) Health Housing Social security Education Othersa

12.4 1.9 0.9 6.1 2.4 1.1

12.5 2.2 1.0 5.6 2.6 1.1

12.8 2.4 1.0 5.5 2.7 1.2

12.9 2.3 1.0 5.4 3.0 1.2

14.0 2.5 1.0 5.7 3.5 1.4

15.6 2.7 0.9 6.4 3.9 1.6

16.0 2.9 0.9 6.4 4.3 1.6

Total expenditures

20.2

20.3

19.9

19.6

21.3

22.4

22.9

Share social/total (%)

61.4

61.7

64.2

66

65.9

69.5

69.9

a

Includes monetary subsidies and social investment programmes for priority groups. Source: DIPRES (2003).

social expenditure rose from 61% of total expenditure in 1990 to 70% in 2002 (Table 9.1), which was higher than the growth rate of GDP. Intense health-sector reforms introduced in 1980 fostered the creation of a private health system, parallel to the public health service. Beginning in 1990, new criteria for health policies were defined, including care for the poorest groups and improvements in the quality of public health. Public investment and expenditure were increased substantially to achieve these goals, and new legislation was developed to coordinate the public and private systems. Despite these improvements, the public system is still weak. More focus is needed on vulnerable groups, especially the elderly. In order to achieve these goals, the government introduced a major public health reform plan (the AUGE) in 2002, which guarantees at least 80% financial coverage for 56 major diseases for the whole population. The plan is estimated to cost the government over US $200 million a year. Chilean education was mainly public up to 1980. In the early 1980s publicly funded schools were decentralized and transferred to municipalities, and private schools were encouraged. The main goal of this reform was to promote competition among schools and increase the costeffectiveness and quality of education. Reforms did increase access to both elementary and high schools, but did not improve the quality of education. Moreover, public expenditure on education was reduced during the 1980s, from 3.5% to 2.5% of GDP, affecting the poor in particular. In 1990, specific education goals were introduced to: (1) improve the quality of education; (2) increase and provide more equal access to education; and (3) promote the participation of different sectors and institutions in education. These changes required a 136% increase in public expenditure for education from 1990 to 1998 (DIPRES, 2001). During 1990 to 1998, the average educational years for the over 15 group rose from 9 to 9.7 years. In terms of quality, tests have shown a systematic reduction in the gap between both subsidized schools and private schools, and between municipal schools and the rest. Housing policy since the late 1970s was focused on the poor, and encouraged private agents to play an active role in design, localization and financing. The State’s main role was

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to provide direct and indirect subsidies. In the early 1980s, there were two housing programmes – social housing and sanitation for houses and neighbourhoods. In both cases, homes were built by private construction firms. As this housing policy was underfinanced, the housing deficit increased during the 1980s. From 1990 to 1998 public expenditure on housing was around 1% of GDP. Housing policy in the 1990s was aimed at reducing the deficit substantially and encouraged the participation of beneficiary families, the private sector, NGOs and community social organizations. Consequently, there were large gains in housing in the 1990s compared with the previous decade, and 53.5% of benefits given out by social programmes were received by the poorest 40% of homes. Benefits received by the poorest quintile grew from 29.5% in 1996 to 32.1% in 1998. While housing quality also rose, there are still around half a million homes with some defect. Finally, in the 1980s little attention was placed on improving productivity in poor areas. Promotion of production was focused on modern sectors of the economy, especially the export sector and bigger companies. At the end of the 1980s, direct support was given through subsidies for small and medium enterprises, but with little concern for low productivity, weak management and technological innovation and poor market access (MIDEPLAN, 1996). In the 1990s, policies changed to support the main state goal of overcoming poverty. FOSIS (the Fund for Solidarity and Social Investment) was created in 1990 to finance productive development among the poor in weaker sectors. Emphasis on decentralization ensured that close to 50% of investment for 1998 was assigned to Regions. Slower economic growth during 1998 to 2001 forced the government to focus on unemployment; 96 000 new jobs were created up to May 2002 (MINTRAB, 2002), and hiring was subsidized to raise employment. Despite such improvements, the social security safety net is still weak. The gap between rich and poor is large in social areas such as education, health and housing, requiring targeted income transfers.

9.2.3 Environmental issues and policies Chile developed a large number of environmental regulations and standards up to 1990, but they were diverse, dispersed among different sectors, fragmented and without coordination. Due to lack of overall coherence, many of the regulations were not applied. Nevertheless, environmental protection received strong support in the 1980 Constitution. Due to poor environmental quality (particularly in Santiago), and the need to defend exports against accusations of ecological dumping, the democratic government of 1990 set up the Special Commission for (Santiago) Metropolitan Region Decontamination and the National Commission for the Environment (CONAMA). In 1994, the General Environmental Framework Law set the foundations for the National System for Environmental Management. Total environment expenditures by CONAMA, the Ministries of Economy and Mining and the Forestry National Corporation are now 50 times more than in 1990 (Brzovic, Miller and Lagos, 2002), having risen to over 2% of the public budget in 2000; see Table 9.2. Environmental


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Table 9.2 Environmental expenditures by objective 1999–2001 All amounts are given in US $1000 Objectives according to CEPA,a 2000 Protection of air and clime Management of liquid waste Management and protection of land, underground water and superficial waters Noise pollution abatement Waste management Protection of biodiversity Other environmental protection activities (including management) Total environmental expenditure

1999

2000

2001b

6337 12 960 41 087

13 440 17 428 60 055

6204 3833 48 693

81 45 568 41 922 149 332

347 43 754 39 654 127 292

305 5352 20 305 70 747

297 286

301 970 155 439

a

Classification of Environmental Protection Activities and Expenditure. Preliminary commitments. Current values at the annual averaged observed dollar (Banco Central). Source: based on FOCUS (2000). b

authorities regulate and control some activities instead of intervening directly. Thus, environmental expenditures can be transferred to the private sector. Despite this progress, policies and programmes for sustainable development still play a secondary role in Chile, resulting in many environmental problems: (1) air pollution, linked to urban areas, industrial activities (pulp and paper, fishmeal), mining and power generation (in specific areas, emissions of different pollutants exceed the national or international norms); (2) high levels of water pollution due to domestic and industrial effluents without treatment; this affects surface water, ground water and coastal seawater; (3) water scarcity at the regional level; (4) inadequate urban development management, high levels of pollution, lack of green or recreational areas, etc.; (5) poor solid-waste management and disposal, particularly hazardous wastes; (6) land degradation, due to poor agricultural and forestry techniques, urban growth and inadequate solid-waste management (this mainly affects agricultural land and river basins); (7) threats to native forests due to overexploitation (increase of forestry activity, coal making, wood collection) and absence of effective protection; and (8) hydro-biological resource overexploitation and biomass exhaustion. The rapid and unmanaged urbanization due to economic growth has led to moderately severe air and water pollution in many cities. Preventive costs, health damages and productivity losses, particularly in Santiago, have been high. Air pollution in Santiago is the most obvious environmental problem in the country (see Figures 9.2 and 9.3 and Tables 9.3 and 9.4), while other cities are also becoming affected (Table 9.5). For Santiago, natural variables, demographic growth and both fixed and mobile air pollution sources are main causes. The total amount of vehicles in Chile has grown from 1.1 million in 1990 to over 2.1 million by 2000. However, important reductions in PM10 and PM2.5 (23.3% and 46%, respectively) have been achieved since 1989. These gains are due to the decontamination

278

National and macroeconomic applications 40 35

alert

30

emergency

25

pre-emergency

20 15 10 5 0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

Figure 9.2. Number of events in the Santiago Metropolitan Region Air Monitoring System. The category ‘alert’ was established in 1997. Source: based on SESMA, www.sesma.cl. 700 600 500 400

Sao Paulo Los Angeles Santiago Mexico City

300 200 100 0 ozone (µg/m3)

CO (ppdm)

PM10 (µg/m3)

Figure 9.3. Comparison of maximum levels of pollution in selected cities (1995–1998). Source: Alliende (2002).

plan, the elimination of 3000 highly polluting buses, the use of natural gas in fixed sources and the introduction of catalytic converters in all new vehicles (50% of cars in Santiago had converters in 1999). Transport contributes the most to air pollution, especially PM10 emissions, the most critical environmental problem in the city, where 25% are emitted directly and another 50% resuspended by vehicles on paved and non-paved roads. This sector is also responsible for 50% of PM2.5, 94% of carbon monoxide (CO), 83% of nitrogen oxides (NOx) and 42% of volatile organic compound (VOC) emissions. Private transport is generally more polluting than public transport in terms of concentration of pollutants per vehicle mile travelled (except for PM10). However, as air pollution in Santiago is subject to climate variables, and pollution strongly


279

Table 9.3 Air pollution in Santiago (1995) Pollutant

CO (ppm)

Ozone (ppb)

PM10a

PM2.5a

SO2a

NO2a

TSPa

Max. Min. Average

35.6 0.1 2.04

224 1 13

302 8 87

174 4 42

161 7 17.8

254 4 64.8

621 31 186.3

Data in μg/m3. Sources: Metropolitan Environmental and Health Service (SESMA) and National Statistics Institute (INE). a

Table 9.4 Air pollution in Santiago (2000) Pollutant

CO (ppm)

Ozone (ppb)

PM10a

PM10–2.5a

PM2.5a

SO2a

Max. Min. Average

19.3 0.1 1.1

162 1 16

230 5 87

105 1 35.8

153 4 34.8

135 1 4.7

Data in μg/m3. Source: SESMA, INE a

Table 9.5 Summary of air quality in Chile’s major cities

City

Region

Excedance of PM10 standard

Arica

I

yearly standard is exceeded

Iquique

I

daily standard exceeded eight times; yearly standard exceeded Antofagasta II daily standard exceeded twice Calama II daily and yearly standards exceeded ValparaísoV daily standard exceeded three Viña del mar times; yearly average very close to being exceeded Santiago metropolitan daily standard exceeded 138 times; yearly average exceeded Rancagua VI daily standard exceeded 11 times; yearly average exceeded ConcepciónVIII daily standard exceeded three Talcahuano times Temuco IX daily standard exceeded nine times Source: summarized from Universidad de Chile (2002).

Other pollutants Main emitting with problems sources probably sulphates no particulates SO2 NO2, SO2, ozone

no information fixed and mobile sources no information fixed sources mobile sources

PM2.5, ozone, CO ozone

streets, vehicles, industry mobile sources

SO2

no information

no

fixed sources

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varies among seasons, the annual average values may be less relevant. Other problem areas in Chile include poor air quality in Concepción-Talcahuano from the steel, petroleum, fishmeal, paper and pulp industries and high levels of ground-level ozone in Valparaíso-Viña del Mar. The Talcahuano environmental recovery plan is in operation, and air monitoring systems have been established in several cities with the goal of identifying saturated zones. Other significant sources of industrial pollution include fossil fuel use, the pulp and paper industry (sulphydric acid) and the fishmeal industry (sulphydric acid and trimethylamine). Since the most significant effects on human health result from fine particles (PM2.5) in air pollution, the Santiago Metropolitan Region was declared saturated with PM10, CO2, O3 and latent of NOx in 1996. A compensation system for particulates from large fixed sources (up to 1000 m3/hr) is in effect for air pollution. Sources emitting less than their goal may sell their emitting capacity. Even though the system has been in place for some years, few trades have occurred. Moreover, there is a general debate as to whether this instrument is appropriate in Chile. In addition, public transport providers must compete for some of the important roads in Santiago, and one key selection parameter is vehicular emission. The rapidly growing domestic waste in Chile is unevenly distributed, with the Metropolitan Region generating 60% of waste while housing only 40% of the population. Water pollution and scarcity are also issues. Factors such as demographic growth, industrialization and concentration of urban areas have contributed to this decline. The problem is most serious in the north (fishing and mining), the metropolitan region of Santiago and central seaboard (sewage and industrial pollution) and coastal areas (Bay of Talcahuano – fisheries, petroleum, and pulp industries), while the south experiences the setback of periodic flooding. The main water quality issue is microbiological contamination. While sanitation services function well, waste treatment facilities are inadequate. Rivers running through Santiago and surrounding (especially coastal) areas are badly affected by the dumping of untreated sewage. Water pollution due to agricultural runoff is a concern. The use of water for agricultural, forestry and aquacultural purposes, as well as the increase in human effluents into the lakes in southern Chile, have greatly increased nutrients, which promote a build-up of algae and a drop in biodiversity. In conclusion, water and air pollution remain as important problems in Chile despite the increasing environmental expenditures, both public and private. The same is true for social issues. Environmental regulation has been hampered by concentration of policy in the centre, with little concern for regional development priorities. Remedies require both new policies to address environmental and social concerns, and improvement in the monitoring and enforcement of such measures.

9.3 Interactions between social, environmental and economic policies Given the issues discussed in the preceding sections, are there major negative interactions or positive synergies between environmental, social and economic policies? This case study seeks to analyse the social effects of environmental policies and the environmental impact of social policies via economic forces.


281

We first simulate environmental policy (reduction by 10% of PM10, SO2 and NO2 emissions through emission taxes), to analyse their impacts on economic, environmental and social variables, and decide which measures are more effective. Next, we simulate the economic, social and environmental impacts of social policy (government income transfers to households). Finally we simulate both policies simultaneously (while maintaining the public savings constant) to identify synergies. We apply the ECOGEM–Chile model, a CGE model for Chile adapted from an OECD CGE model (Beghin et al., 1996). This CGE model (Appendix A, Section 9.8), is a static multisector model with two kinds of labour, five quintiles of income, an external sector and specific productive factors. It is savings-driven, with energy-input substitution to reduce emissions, as emissions are related to the use of different inputs and not only to production levels. The main source of information is the 1996 Chilean social accounting matrix (SAM), based on the most recently available input/output matrix for 1996 (Banco Central de Chile, 2001). The study is denominated in billions of pesos at 1996 purchasing power.3 We assume zero capital mobility across sectors and adjustment within sectors in the short run. Long-term values are used for the income, substitution and other elasticities from the relevant international literature, giving more flexibility and realism to the adjustment process. However, investment and capital accumulation processes as a function of relative returns are not included due to the static nature of the model, and long-term elasticities will only minimize this flaw. With these parameters, the scenarios modelled here should account for medium-term effects. Although full employment is assumed, we also create a scenario that analyses the effects of high unemployment. There are two types of emission coefficients: input-based and output coefficients; 13 different pollutants are identified. Toxic effluents are segregated by medium: air, water and soil (TOXAIR, TOXWAT, TOXSOIL). They contain mineral and industrial chemicals, fertilizers and pesticides, paints, etc. Bio-accumulative pollutants are also segregated by medium: air, water and soil (BIOAIR, BIOWAT, BIOSOIL). They contain metal elements such as aluminium, arsenic, copper, lead, mercury, zinc, etc., and they have a significant longterm risk to life. Other air pollutants include SO2, NO2, VOCs, CO and PM10. Other water pollutants include BOD (biological oxygen demand) and TSS (total suspended solids).

9.3.1 Environmental policies We analyse the impacts of a 10% reduction in PM10 emissions by using emission taxes (the main target of the air pollution policy). This reduction level is easily achieved without high abatement costs, and is compatible with the current economic context of high unemployment. Furthermore, expected revenues associated with environmental taxes are similar to financial requirements for employment policy. We replicate the same exercise for NO2 and SO2 emissions, looking for efficiency gains, enhancing positive results and reducing

3

Unpublished mimeograph by R. O’Ryan, C.J. De Miguel, S. Miller and C. Lagos (2001), ‘A social accounting matrix for Chile 2001’.

282


Table 9.6 Macroeconomic impacts of environmental taxation Taxation on

PM10

SO2

NO2

Real GDP Investment Consumption Exports Imports

− 0.2% [− 0.1%] 0.8% [0.9%] − 0.6% [− 0.5%] − 1.1% [− 1.0%] − 1.0% [− 0.9%]

− 0.2% 0.6% − 0.5% − 1.0% − 0.9%

− 0.2% 0.7% − 0.6% − 1.0% − 0.9%

Results for PM10 with high unemployment are presented in square brackets.

Table 9.7 Sectoral impact of environmental taxation

Construction Electricity Renewable resources Wood products Gas Load and passenger transport Other transport Oil and gas extraction Coal Oil refinery

PM10

SO2

NO2

0.7% [0.8%] − 0.1% [0.0%] − 0.7% [− 0.6%] − 0.7% [− 0.6%] − 0.8% [− 0.7%] − 2.2% [− 2.1%] − 2.3% [− 2.1%] − 4.1% [− 4.0%] − 5.2% [− 5.0%] − 9.7% [− 9.6%]

0.6% 0.3% − 0.6% − 0.6% − 0.8% − 2.1% − 2.2% − 4.3% 1.1% − 9.8%

0.6% 0.3% − 0.6% − 0.6% − 0.8% − 2.1% − 2.2% − 4.3% 1.1% − 9.8%

Results for PM10 with high unemployment are presented in square brackets.

negative ones. Apart from causing acid rain, NO2 and SO2 are the main chemical components of PM2.5 – the fine fraction included in PM10 that causes most health problems. The higher public budget link is not offset by environmental tax revenues, leading to increased public savings. Thus, new taxes are imposed without any other taxation/subsidy compensation. Table 9.6 shows moderate impacts on all macrovariables despite the adjustment process that follows taxation. Real GDP and consumption are moderately reduced, as well as exports and imports, which are close to 1%. Some significant sectoral impacts can be observed in Table 9.7. Emission taxes increase revenues, raising public savings by around 14%. Despite marginally reduced household and enterprise savings, global savings rise. Increases in savings raises investment, which is channelled to the economy mainly through the construction sector, raising sector output by 0.7%. The electricity sector also marginally benefits from these policies, since part of energy demand is substituted from oil and gas toward electricity (− 0.1%–0.3%). Transport, oil and gas extraction and oil refining suffer the highest negative impact in these simulations, reducing their sectoral output by 2.1%–2.3%, 4.1%–4.3% and 9.7%–9.8%, respectively.


283

Table 9.8 Environmental impact of environmental taxation

TOXAIR TOXWAT TOXSOIL BIOAIR BIOWAT BIOSOIL SO2 NO2 CO VOCs PART BOD TSS

10% reduction of PM 10

10% reduction of SO2

10% reduction of NO2

− 0.6% − 1% − 0.4% − 1.4% 0.2% [0.3%] − 0.4% − 10.1% − 10% [− 9.9%] − 9.5% − 1.1% [− 1%] − 10% − 0.4% − 8.9% [− 8.8%]

− 0.6% − 0.9% − 0.4% 0% 0.6% − 0.4% − 10% − 9.9% − 3.5% − 1% − 9.3% − 0.4% 2.7%

− 0.6% − 1% − 0.4% 0% 0.6% − 0.4% − 10.2% − 10% − 3.5% − 1.1% − 9.4% − 0.4% 2.7%

Results for PM10 simulation with high unemployment are presented in square brackets, when different.

Table 9.9 Environmental impact of PM10 taxation


Total effect

Production effect

Demand effect

− 0.6% − 1% − 0.4% − 1.4% 0.2% − 0.4% − 10.1% − 10% − 9.5% − 1.1% − 10% − 0.4% − 8.9%

− 0.6% − 0.8% − 0.4% − 1.5% − 2.2% − 0.4% − 7.8% − 7.7% − 8.5% − 1.3% − 7.8% − 0.4% − 8.9%

− 2.8% − 6.3% 0% − 0.1% 0.7% 0.1% − 16.5% − 16.5% − 16.3% − 0% − 16.5% − 0% − 10.3%

From an environmental point of view, Tables 9.8 and 9.9 and Figure 9.4 show that almost all emissions can be reduced by taxing PM10 emissions, except for bio-accumulative effluents into water, which increase marginally due to improvements in the construction sector. Furthermore, NO2 and SO2 emissions fall by over 10% with PM10 taxes. The latter indicates strong links between different pollutants, especially among air pollutants. Taxing PM10 also shows greater positive environmental impacts than SO2 or NO2 taxation. The

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Table 9.10 Impacts on utility of taxation on PM10 emissions

1st quintile 2nd quintile 3rd quintile 4th quintile 5th quintile

PM10

PM10 + unemployment

− 0.6% − 0.6% − 0.5% − 0.5% − 0.2%

− 0.5% − 0.5% − 0.5% − 0.4% − 0.2%

4.0 2.0 0.0 –2.0 –4.0 –6.0

PM10

–8.0

SO2 NO2

–10.0

S

D

TS

BO

RT PA

CS O V

2

CO

O

2

X

N

A X TO

TO

W TO AT X SO I BI L O A IR BI O W A BI T O SO IL SO

IR

–12.0

Figure 9.4. Environmental impact of environmental taxation Note that PM10 columns show the impacts on all pollutants when taxing PM10; the same applied for SO2 and NO2, respectively.

latter presents some increments on water effluents due to sectoral reaccommodation of production. Vis-à-vis social effects, the simulations show a slight increase in employment (related to the slight decrease in wages), due to higher demand for labour in construction, offset by contractions in other sectors. A more positive effect on employment is seen when environmental taxes (on PM10) are applied in a high-unemployment scenario. There is also a moderate negative effect on household incomes, which are reduced by 0.6% for all quintiles (− 0.5% in the case of high unemployment). The effects for SO2 and NO2 taxes are similar. If another welfare measure is used (such as the utility function), this policy is slightly regressive, as part of the enterprise adjustment to the new environmental taxation involves wage reduction and consumer price increases, thereby affecting lower-income consumption relatively more (Table 9.10). Finally, environmental policies have some negative social impacts, especially on welfare – partly because decreasing marginal utility of income is assumed. By contrast, all benefits from environmental gains (such as reduction in health costs, productivity gains, etc.) are not included. Thus, negative social and economic impacts are overemphasized.


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We may conclude that: (1) taxing key pollutants can reduce global pollution more effectively than taxing other effluents – e.g. PM10 taxes yield superior environmental results with fewer macro, sectoral or social consequences; (2) there are strong links between different pollutants, and tax effects need to be carefully differentiated; and (3) macroeconomic impacts are low and negative, but sectoral effects (positive and negative) can be strong. Therefore, policy and adjustment periods need to be flexible. Environmental tax revenues may be used to compensate the losers directly or to reduce/eliminate a distorting tax (achieving double dividends). Through careful targetting, taxing bads instead of goods could reduce pollution without economic and social losses. We may also conclude that (4), with high unemployment, the economy adjusts better to an environmental tax shock.

9.3.2 Social policies The simulated social policy consists of an increase in transfers to households by 8.4%, which is equivalent to the cost of 100 000 new jobs created directly by the government, or an actual unemployment reduction from 10% to 8.2%. Public transfers would increase from 23% to 25% of government expenditure, with no offsetting revenue, thereby reducing government savings. The distribution of transfers is held constant at current levels: first quintile, 27.3%; second quintile, 26.6%; third quintile, 22.3%; fourth quintile, 17.9%; and the richest quintile, 5.9%. The macroeffects are very minimal (Table 9.11); GDP is not affected. Investment falls by almost 1% due to the reduction of government savings (of more than 14%). However, consumption grows due to higher disposable incomes for almost all households. The construction sector is the most negatively affected, due to reduction in investment. The gas, hydraulic/water and load and passenger transport sectors benefit slightly from this social policy. Social impacts are positive, with real income for almost all quintiles increasing and the poorest improving the most. Impacts on utility are very similar. Finally, in terms of environmental effects, there are slight increases, mainly in air emissions. The demand effect is generally negative for environmental quality, whereas the production effect is positive (due to the construction slowdown). However, all impacts are small. This social policy has very low impacts on the environment, while the sign depends on the specific pollutant.

9.3.3 Joint policies: social and environmental In the previous exercises, the environmental policy applied did not have major social impacts, and vice versa. Furthermore, a double dividend (social and environmental) did not exist. However, there seemed to be a trade-off among social and environmental policies/ impacts. Therefore, we study joint social–environmental policies – taxes to reduce PM10 emissions by 10% and higher government transfers to homes using those tax revenues (thus keeping real government savings constant). Macroimpacts are an average of the results of applying social and environmental policies independently (Table 9.12). The negative effect of environmental policy on consumption is

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Table 9.11 Impacts of a social policy consisting of an increment of transfers to households Macrovariables

real GDP investment consumption exports imports

0.0% − 0.8% 0.4% − 0.1% − 0.1%

Sectoral production output

construction electricity renewable resources wood products gas water load and passenger transport other transport oil and gas extraction oil refinery

− 0.7% 0.1% 0.0% 0.0% 0.2% 0.2% 0.2% 0.0% 0.0% 0.1%

Households, real income

first quintile second quintile third quintile fourth quintile fifth quintile

Environmental variables emissions

TOXAIR TOXWAT TOXSOIL BIOAIR BIOWAT BIOSOIL SO2 NO2 CO VOC PART BOD TSS

3.2% 1.7% 1.0% 0.4% 0.0% − 0.1% − 0.1% − 0.1% − 0.1% − 0.7% − 0.1% 0.1% 0.1% 0.1% 0.0% 0.1% − 0.1% 0.2%

Table 9.12 Comparative macroeconomic impacts

Real GDP Investment Consumption Exports Imports

PM10

Transfer

PM10+transfer

− 0.2% 0.8% − 0.6% − 1.1% − 1%

0% − 0.8% 0.4% − 0.1% − 0.1%

− 0.2% − 0.1% − 0.2% − 1.2% − 1.1%


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Table 9.13 Comparative sectoral impacts

Construction Electricity Renewable resources Wood products Gas Water Load and passenger transport Other transport Oil and gas extraction Oil refinery

PM10

Transfer

PM10+transfer

0.7% − 0.1% − 0.7% − 0.7% − 0.8% − 0.1% − 2.2% − 2.3% − 4.1% − 9.7%

− 0.7% 0.1% 0% 0% 0.2% 0.2% 0.2% 0% 0% 0.1%

− 0.1% 0% − 0.6% − 0.8% − 0.5% 0.1% − 2% − 2.3% − 4.1% − 9.6%

Table 9.14 Comparative social impacts Real disposable income

PM10

Transfer

PM10+transfer

1st quintile 2nd quintile 3rd quintile 4th quintile 5th quintile

− 0.6% − 0.6% − 0.6% − 0.6% − 0.6%

3.2% 1.7% 1% 0.4% 0%

2.6% (2.5%) 1.1% (1.1%) 0.4% (0.3%) − 0.2% (− 0.1%) − 0.6% (− 0.2%)

Utility levels are presented in brackets.

mitigated, while the negative investment effect due to the social policy is offset. Macrovariables suffer from a slightly negative impact. At a sectoral level, the combined policies yield results that are the average of individual environmental and social policies (Table 9.13). Social impacts are very positive (Table 9.14). Employment increases slightly and income distribution improves. There is a reduction in real income of the wealthier 40% of the population. In terms of utility, the results are quite similar. Environmental impacts of the joint policies are good (Table 9.15). Nine of the 13 types of emissions are lower than when applying the environmental policy only. In the other four cases, mitigation is close to the highest levels achieved by the separate policies. In conclusion, it is better to combine environmental and social policies. Macro and sectoral impacts maintain their effects in the worst scenario, but both social and environmental variables improve even more. Nevertheless, the small cross-impacts of environmental/social policies indicate the value of separately identifying potential losers for later compensation or side policies.

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Table 9.15 Comparative environmental impacts


PM10

Transfer

PM10+transfer

− 0.6% − 1% − 0.4% − 1.4% 0.2% − 0.4% − 10.1% − 10% − 9.5% − 1.1% − 10% − 0.4% − 8.9%

− 0.1% − 0.1% − 0.1% − 0.1% − 0.7% − 0.1% 0.1% 0.1% 0.1% 0% 0.1% − 0.1% 0.2%

− 0.8% − 1.1% − 0.6% − 1.5% − 0.4% − 0.6% − 10.1% − 9.9% − 9.5% − 1% − 10% − 0.6% − 8.8%

9.4 Chile case study conclusions During the 1990s, Chile sought to improve environmental and social standards. Further improvements will have increasing marginal costs. Therefore, innovative new approaches are required, including combining different policies so as to enhance synergies among them. This case study presented an empirical application of the CGE model, ECOGEM–Chile, to assess economic, environmental and social linkages. Six different policies are simulated: three environmental policies that impose taxes on air emissions, aiming to reduce 10% of total PM10, SO2 and NO2 emissions, respectively; one social policy that increases government transfers to households; a joint social–environmental policy package, where the environmental tax on PM10 and the social transfer policy are combined (keeping public savings constant – i.e. environmental taxes finance social transfers); and PM10 taxation with high unemployment. Taxing PM10 emission yields better environmental results than taxing SO2 and NO2, without substantial differences in the macro, sectoral or social results. With the PM10 environmental policy, the macroeconomic impacts are slightly negative, but sectoral effects (positive and negative) can be strong. Therefore, policy makers should consider a flexible policy with adjustment periods. Taxing environmental bads instead of goods yields good environmental results without economic and social losses. With high unemployment, an environmental tax shock is better absorbed by the economy, because firms have more freedom to adjust their production functions through the labour market. The impacts of social policy on environmental quality are very low, although the sign depends on the specific pollutant. Overall, the evidence suggests that environmental policies may have social impacts, but not vice versa.


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Since cross-effects are relatively small, policy makers should focus on the specific policy under consideration. Nevertheless, social and environmental policy makers should coordinate among themselves, as it is possible to improve some results by combining both strategies, i.e. the mix of policies may improve overall results. Thus, compensating potential losers might increase their acceptance of environmental policies. These results show that general equilibrium modelling is useful for systematically and holistically analysing different economy-wide policies and their impacts on the Chilean economy. Winners and losers may be identified, including the magnitudes of gains and losses. The results are not always straightforward, i.e. indirect effects are also relevant.

9.5 Economy-wide policies and deforestation in Costa Rica This case study seeks to make development more sustainable in Costa Rica by studying links between deforestation and economy-wide policies.

9.5.1 Background The economic analysis of environmental issues relies mainly on project-level studies, using cost–benefit analyses and environmental assessments. Chapter 7 showed how growthoriented economic reform policies could interact with overlooked imperfections, such as market failures, policy distortions and institutional constraints, to cause environmental harm. General equilibrium analysis helps to trace the socioeconomic and environmental effects of economy-wide policy reforms. When such comprehensive methods are not possible in developing countries, where data and skills are scarce, partial approaches that help to identify the most important impacts of economy-wide policies are frequently used. Because the full consequences of a policy are not traced, both quantitative and qualitative results of the partial equilibrium model may be wrong. For example, taxes that are not ‘lump sum’ may carry over from the sector for which they were intended into other sectors of the economy and affect consumption and production decisions there as well. In this context, the main purpose of this study is to investigate the effects of economy-wide policies in Costa Rica on forest areas and the environment (Persson, 1994). We also seek to determine whether new measures involving the allocation of property rights to these forests will yield different results when analysed using a general equilibrium model rather than a more conventional partial equilibrium approach. In the remainder of this section, the main issues, analytical approach and results are summarized. The following section describes previous work on Costa Rica and the environmental priorities. The applicability of computable general equilibrium (CGE) models to such problems is discussed next, followed by further details of the model and data used here. Finally, the last two sections summarize the chief results and conclusions of the study. Appendix B (Section 9.9) provides model details. Deforestation and soil erosion are major environmental problems in Costa Rica (see Table 9.16). The CGE model used here highlights economic activities that affect

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Table 9.16 Percentage of total land area in forests and agriculture

Agriculture Forest

1963

1973

1986

30% 67%

40% 57%

57% 40%

Source: Solórzano et al. (1991).

deforestation. It goes beyond standard approaches in two key respects. First, it can simulate the effect of introducing property rights on forest resources, thus encouraging sustainable management of forests by private individuals who value future returns to forestry. Second, it includes markets for logs and cleared land: loggers deforest to sell timber to the forest industry and for exports, while squatters clear land for agricultural production and sale to the expanding agriculture sector. A fairly standard CGE model is used. The tradable sectors – forestry, agriculture and industry – are price takers in the world market, while infrastructure and services produce non-traded output. To focus on the natural-resource sectors, the domestically mobile factors include, aside from capital and (skilled and unskilled) labour, cleared land and logs. The supplies of both labour and capital are exogenous. The demand for these factors arises from the producing sectors (agriculture, industry, etc.) and from deforestation by loggers and squatters. The supply of ‘cleared’ land is initially based on the total deforested land area. However, additional cleared land is made available from increased deforestation. This rate of land clearing depends on the definition of property rights as well as on taxes (or subsidies) that affect the forest and agricultural sectors. In addition, the expansion of squatting activities augments the cleared land factor. Agricultural production provides the demand for cleared land. Poorly defined property rights in Costa Rican forests play an key role in deforestation. The model shows how correction of this market failure would reduce deforestation. If property rights are well defined and the interest rate is exogenous, the value that loggers assign to preserving the forests is crucial. In order to stop deforestation, the benefits from preserving the forests must be significantly higher than the value of the logs and the cleared land. Tax policies may generate unexpected side-effects, while substitution effects between inputs in the producing sectors may be important. Therefore, when impacts of macroeconomic policies are investigated, the general equilibrium approach generates results that are different from those derived from a partial equilibrium analysis.

9.5.2 Status of forests in Costa Rica Deforestation in Costa Rica is proceeding at a rapid pace. MRN (1990) mentions the following economic and ecological benefits that Costa Rica may lose if deforestation continues: access to construction materials and other wood products, unchecked species


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of plants and animals that have possible and future uses for consumption and industrial production, recreation and eco-tourism, control of erosion and sedimentation and education and research possibilities. The greenhouse effect and concerns about the rich biological diversity in Costa Rica are important to the global community. Deforestation and erosion are the main environmental problems in the country (Blomström and Lundahl, 1989; Foy and Daly, 1989). Most of the deforestation has occurred since 1950. If deforestation continues at the current rate, the commercial forests of Costa Rica will be exhausted within the next decade. The life zones with the highest rates of deforestation are the tropical wet forests, which are also ones in which biodiversity levels are highest (Solórzano et al., 1991). Deforestation takes place in several stages (Carriére, 1991; Keogh, 1984). First, a logging company involved in highgrading clears a vehicle tract to extract lumber. Then, the road is improved by the government due to pressures from lobbying groups, and this in turn enables local peasant families to clear and use the remaining forest for subsistence agriculture until the decreasing yields force them to sell or abandon the land (depending on whether it is titled or not). The land is still suitable for pasture and is therefore sold to cattle ranchers by urban-based real estate companies. After a few years, the land is almost completely degraded and unsuitable for any kind of economic use. The Costa Rican government is taking steps to preserve the forests. More than 13 000 square kilometers have been designated as national parks, although some deforestation was encouraged to diversify the country’s production away from coffee and banana crops (Biesanz, Biesanz and Biesanz, 1987). Deforestation in Costa Rica is caused by several factors, given in the following. (1) The timber industry may be responsible for deforesting as much as 20 000 hectares annually. Logging requires a special government permit, but about half of the trees are cut illegally. Domestically cut logs are processed locally and are typically used in construction. Exports of wood and wood products are small and imports are negligible. The import tariff on logs is 5%. The efficiency in the forestry sector is low, and only a few species are commercially used. About 54% of the logs are processed, of which about half finally reach the market (MRN, 1990). The main part of the logs used in the timber industry are bought from sources other than the industry itself. (2) Banana firms and other companies are expanding their plantations rapidly. The main products cultivated in Costa Rica are rice, coffee, fruits, sugar cane, beans, maize and sorghum (Hugo et al., 1983). The Costa Rican tax structure for income and property taxes is regressive. Sales and other indirect taxes constituted 70% of total tax revenues in 1970. Although property taxes are low (in some cases about 1% of market value), tax evasion costs the country approximately 100 billion colones a year. One remedy may be to raise land prices by increasing land taxes, increase tax collection rates and prosecute tax evaders more effectively. (3) Cattle ranchers have expanded their activities rapidly at the expense of forested areas in recent decades. However, this type of land conversion may be limited now because most of the land that can be sustainably used for pasture has already been cleared. In the 1950s and 1960s, there was a large increase in investment in cattle, encouraged by foreign aid and investment as well as government credit and provision of infrastructure. This increase of cattle ranching caused rapid

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deforestation. The pasture trend peaked in the 1970s, but since then profits have decreased. Over 70% of the farmland is in pasture, while only 2.5% is in coffee and 1.1% is in bananas (Biesanz et al., 1987). (4) Squatting is taking place on both privately owned and government land. Some squatters produce agricultural outputs, but others sell the cleared land to cattle ranchers or other landowners. Buyers who buy ‘in good faith’ from squatters are not prosecuted. About twice as much is paid for cleared land as is paid for forests. By clearing the land, it is possible to get formal ownership of it (Blomström and Lundahl, 1989). Squatting by smallholders is a less significant part of the overall deforestation, although it may be locally important.

If ownership may be obtained with no costs other than those of clearing the land, the forests can be seen as a type of common property, while the cleared land is perceived as traditional private property. However, it is not the traditional case of undefined property rights and an open-access resource. We are here looking at insecure land tenure. This implies that there is no crowding effect on the stock of the resource, which is what occurs when each agent maximizes his own profit without taking into account the effect on the stock of the resource. There is a form of short-term property rights when deforestation occurs, but the property rights to the standing forests are not protected. The logger or squatter will continue to deforest only until the marginal cost of deforestation equals the marginal revenue, because of this structure of property rights. The social cost of deforestation will then be higher than the private cost since ‘the world’s’ willingness-to-pay for the preservation of the Costa Rican forests will not be included in the private cost. Thus, deforestation would be driven by the difference in private and social objectives. For example, the loggers’ main interest may be the profitability of the logging operation without much consideration about future, alternative uses of the land. Deforestation may also be caused by high private discount rates that diminish the future value of forests. The impacts of tropical forests are often more significant in the long term than in the short term. However, the regenerative capacity of tropical forests is low, and the discounting of future environmental benefits often makes it more profitable to harvest forest resources as quickly as possible. Forest investments, such as replanting, take a long time to yield returns, and individuals therefore find little attraction in conservation and reforestation activities. In many developing countries, private market rates are very high and often exceed the rate that would be socially justifiable. Poor people often face even higher discount rates because of credit constraints. Finally, in addition to sectoral policies, economy-wide tax policies may also have a significant effect on deforestation rates.

9.6 Modelling approach To summarize, the main reasons for deforestation and thereby erosion are as follows: (1) the price of land is too low because the full social opportunity value of rain forests is not included; (2) undefined property rights make the private cost of deforestation lower than the social cost; (3) discount rates may be too high, implying that future gains from


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forests are lower than the gains from deforestation today; and (4) impacts of economywide policies.

9.6.1 Relevant past research CGE models have been applied before to environmental problems, mainly those involving air pollution and pollution taxes. Some relevant CGE models are briefly reviewed below. Bergman’s (1990a, 1990b) model is designed to simulate the effects of environmental regulation and energy policy on the Swedish economy. The environmental market failure is corrected by the creation of a market for emission permits. The cost of emission permits for carbon dioxide, sulphur and nitrogen is included in the cost functions. Jorgensen and Wilcoxon (1990) analyse the economic impact of environmental regulations in the USA by simulating long-term growth with and without environmental regulations. The abatement cost share in total costs is estimated for each industry, as are the share of investment in pollution control equipment and cost of pollution control devices in motor cars. The model is run with and without these costs to estimate economic impacts. There are few examples of CGE models dealing with the impact on the economy of overexploitation of natural resources. Panayotou and Sussengkarn (1992) construct a model against the background of environmental problems in Thailand. The sources of the environmental issues are economic growth, exchange rate problems and government policies promoting deforestation. This implies that every unit of production in each sector generates a fixed amount of air pollution or deforestation. The environmental impacts are not part of the model per se, since the environmental degradation or improvement is not fed back into the model so as to affect future production and consumption decisions. The results include the findings that export taxes on rice and rubber increase investment in soil conservation, increase the use of agrochemicals and shift land from rubber to rice. Little work has been done on modelling undefined property rights in a general equilibrium context, where the results may differ from those of a partial equilibrium model. Devarajan (1997) suggests that it may be useful to include a partial equilibrium model in the general equilibrium framework by first removing the first-order condition that labour is paid the value of its marginal product in some sectors and then replacing it with a condition that reflects the suboptimal behaviour of the sector. This helps to analyse the effects of policy interventions on deforestation. The model has to be dynamic to include both stock and flow effects of deforestation. Unemo (1996) models the suboptimal use of land in Botswana that is caused by overgrazing of cattle due to undefined property rights to the land (see Section 8.6.1). In order to model property-rights-related behaviour in Costa Rican forests, we assume that the private cost of deforestation is lower than the social opportunity value of the forests when property rights are undefined. When property rights are defined, the social value of the rain forests is incorporated in the utility functions of the squatters and therefore in the private cost of deforestation. This facilitates analysis of the role of undefined property rights, following Chichilnisky (1993).

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9.6.2 General features of the model This open-economy CGE model is static, although it has certain implicit dynamic features because the discount rate is included in the future valuation of forested land. It differs from the standard approach of CGE modelling by including undefined property rights and modifying the functioning of markets for logs and cleared land. Land cleared by squatters is assumed to be sold to the agricultural sector. The model has two types of sectors. The tradable producing sectors (T sectors – forest, agriculture and industry) are assumed to be price takers on the world market in the standard Heckscher–Ohlin fashion. The non-tradable producing sectors (N sectors) are infrastructure and services. Further, there are two sectors that clear land: loggers, who supply the forest industry and exports, and squatters, who sell land to the agriculture sector. The domestic intersectorally mobile production factors are unskilled labour (ULABOUR), skilled labour (SLABOUR) and capital (CAPITAL). Logs (LOGS) and cleared land (DLAND) are specific to the forest and agriculture sectors, but logs can be traded on the world market. No reafforestation is possible. Key elements of the model are summarized below – mathematical details are given in Appendix B, Section 9.9 and Persson and Munasinghe (1995). Factor market equilibrium and the stock of forested land The supplies of both labour and capital are assumed to be exogenously given, and for factor markets to clear these supplies must equal the demands for labour and capital, respectively (see Figure 9.5). Demands arise from producing sectors and from squatters and loggers. The demand for each production factor (capital or labour) within the T and N sectors, as well as deforestation sectors, is given by the partial derivative of the cost function for the relevant sector with respect to the price of the same production factor. Both loggers and squatters generate demand for unskilled labour for deforestation, but only loggers generate demand for capital. Costa Rica’s total area is divided into cleared land and forested land. Cleared land is produced through deforestation, depending on the definition of property rights, taxes and subsidies on the factors of production, and profits in the forest and agriculture sectors. Logs are assumed to be tradable. Thus, the demand for forest land by the logging sector and the world market price determine the rate of deforestation. This demand is equal to the partial derivative of the logging cost function with respect to the user cost of logs plus the net export of logs. The supply of cleared land includes the stock of cleared land plus deforestation by squatters. The demand for cleared land (for agriculture) is set equal to the partial derivative of the agriculture sector cost function with respect to the user cost of cleared land. A given user price is greater (smaller) than its supply price by a percentage tax (subsidy). Technology, costs and producer behaviour Production factors are aggregated into a composite factor input Y. Next, DLAND is combined with CAPITAL to yield an aggregate, R, which in turn is combined with LOGS


295

deforestation land, logs

labour, capital

factor demand

factor supply factor markets

factor costs

wages, rents

demand for intermediate goods

producers

households

sales revenues

consumer expenditure

product markets supply of produced goods

imports

exports

consumption of final goods

rest of world

Figure 9.5. Representation of flows in the Costa Rica model.

to generate M. The latter is combined with SLABOUR to produce V, which is combined with ULABOUR to yield the composite Y. This aggregation uses a constant elasticity of substitution (CES) production function with constant returns to scale. Inputs and output are linked by a Leontief production function for each sector. Because the technology exhibits constant returns to scale, the marginal cost and the average cost of production in a given sector can be expressed as a linear function of prices, relevant input–output coefficients and indirect tax rates. Producers are assumed to maximize profits. The producer output prices, Pi , in the tradables-producing sectors are equal to world market prices. Assuming perfect competition, this implies that pure profits are non-positive and output is non-negative (positive only if pure profits are zero). In the non-tradables-producing sectors, the sector-specific capital is endogenously adjusted so that price equals marginal cost. Prices, domestic demand, foreign trade and market clearing For goods produced in the tradables-producing sectors, the domestic producer price is equal to the world market price, and, in the non-tradables-producing sectors, the domestic user

296


price is equal to the producer price times the tax rate. The intermediate demand for a good is given by the technology assumptions. Domestic final demand is given by a linear expenditure system, derived from the consumers’ utility maximization. To equilibrate the market for a good, the net export for that good is defined as the difference between domestic supply and demand. Deforestation sectors Two sectors are responsible for deforestation. They interact with the rest of the economy through their demands for capital and labour by supplying forest products and clearing land for the rest of the economy and through changes in the relative prices of factor inputs and sectoral outputs. The logging sector The logging sector is assumed to have capital-intensive technology and to exhibit decreasing returns to scale – to reflect reductions in available forest area and illegal logging. The production of logs is assumed to depend only on labour and capital. A log-linear production function is used. Returns to the production factors fall with increased deforestation. Increased deforestation for logs is assumed not to affect the returns to deforestation for land, and vice versa. However, increased deforestation for logs lowers yields in the logging sector, and increased deforestation for land reduces returns in the squatting sector. With undefined property rights, loggers consider only the private cost of deforestation. When property rights are well defined, the opportunity value of saving the forests is included in the loggers’ cost function. Squatters The forested land cleared by squatters is seen as a common property, although there is no crowding effect because the stock of forested land is not included in the squatters’ production function. The base case assumes undefined property rights (Johansson and Löfgren, 1985). The squatters’ production function for cleared land increases monotonically with labour inputs. Their total revenue from clearing the land is the price paid for cleared land. Part of the land cleared by squatters is sold to the agriculture sector. The rest is used for subsistence agriculture by the squatters. However, because both activities occur, the returns at the margin must be the same in each case. The squatters are assumed not to sell the timber or use it for other purposes, such as fuel. The squatters’ total private cost to clear the land depends only on the amount of labour needed in order to clear the land when property rights are undefined. This is the private cost, which does not include the future value of the forests and the cost of environmental damage. Therefore, the total social cost of deforestation is this private cost plus the future benefits from cleared forests that are foregone by clearing the land today. The future value of the forests is assumed to be greater than the value of the forests today. The analysis of the definition of property rights can then be accomplished through the simulation of two regimes. In the case of undefined property rights, the present-day squatters do not take the future value of the forests into account. When property rights are well defined, the squatters

9 CGE modelling applications value ($)

297

MCWPR opportunity value (H-value) MCUPR MR

dWPR

dUPR

deforestation (area)

Figure 9.6. Definition of property rights.

own their land and take the future value of the forests into account. The owners of forested land (that is, the ‘squatters aware of the future’) decide whether to preserve the forests or clear the land. When property rights are undefined, no market for the forests is available to squatters. A simple partial model of land clearing by squatters (in which each squatter receives an equal share of the private profits) is used to show that land will be cleared until marginal cost equals marginal revenue. This result corresponds to maximization of private profit, given insecure land tenure. When property rights are well defined, there is a market for the forests. The squatters take the future value of the forests into account, and they can choose to clear forested land or to preserve the forests. This is consistent with the condition for socially optimal forestry – that a tree should be harvested when the market value is equal to the shadow value (Hellsten, 1988). This result corresponds to the optimization of net social benefits. The foregoing suggests that more land is cleared when property rights are undefined (point dUPR) than when they are well defined (point dWPR) – see Figure 9.6. This is because the squatters’ marginal cost of deforestation is lower when property rights are undefined (curve MCUPR) than when property rights are well defined (curve MCWPR), and the cost includes the future value of the forests. MR is the marginal revenue curve. When property rights are well defined, deforestation is increased by (1) a change of technology toward more efficient use of labour in the production of cleared land; (2) an increase of the time preference rate; and (3) an increase in the supply price of cleared land. Conversely, deforestation falls with rises in (1) future value of the forests and (2) price of labour. When property rights are undefined, the clearing of land is not affected by the future value of forests and the rate of time preference. The effects of other variables are the same as in the earlier case. When property rights are well defined, the profit maximization condition for squatters includes the opportunity value of saving the forests for alternative uses or deforestation in a later time period. When property rights are undefined, this effect is absent, since future tenure is uncertain.

298


Macroeconomic closure and measures of welfare The current account is assumed to be constant, and the surplus is defined as the sum of net exports. There are three welfare measures: disposable income (implicitly determined from the current account), green gross domestic product (GDP, determined as the sum of factor incomes plus a term that diminishes with increased deforestation to reflect the negative welfare effects) and utility (determined from the consumer utility function). Utility maximization results in a linear expenditure system for goods, based on a transformed Cobb–Douglas utility function.

9.6.3 Base case data, assumptions and limitations of the model The data come from Solórzano et al. (1991), the national accounts (Banco Central de Costa Rica, 1990) and adjustments made by Raventós (1990). The input–output matrix was calculated from the disaggregated data used in Raventós (1990). Resource flows are shown in Figure 9.7. The substitution elasticity between land and capital in the agriculture sector was set at 0.5. The substitution elasticity between the capital aggregate R and LOGS was assumed to be 0.8 in the forest sector, and the substitution elasticity between the aggregate M and SLABOUR was set at 0.8 in all producing sectors. Compared to other studies, such as Bergman (1990a, 1990b), these values appear reasonable. The remaining elasticities (involving land and logs in sectors that do not use those factors) were set to zero, which is consistent with a fixed coefficient (Leontief) technology. The parameters in the production functions for squatters and loggers are judgement-based estimates, assuming a labour-intensive technology for the squatters and a capital-intensive technology for the loggers. There are some limitations. First, because of data adjustments, the results are more indicative than precise quantitative measures. Second, the static model provides comparative snapshots of the economy. Third, other linkages are not considered – e.g. migration, population growth, reafforestation, erosion and other external effects of deforestation.

Sector

Forest Agriculture Industry Service Infrastructure Squatters Loggers Net exports

Forest Agriculture Industry intermediate inputs Service Infrastructure Squatters

final demand

+lsq

Loggers

+logf

Labour Capital

–lgl –lgk

Land

deforestation sectors

Domestic Total demand demand

–lsq –lv

deforestation demand +lsq

+lgl +lgk

factor income

+lv

Indirect taxes indirect taxes Total

total production demand

output producing sectors

government revenue deforestation

total final demand

Figure 9.7. Resource flows and data adjustments: lsq = labour input in squatting; logf = logging; lgl = labour input in logging; lgk = capital input in logging; lv = land value.


299

9.7 Main findings of the Costa Rica study 9.7.1 Numerical results Some CGE results differ from what might be expected from the partial equilibrium framework discussed earlier due to substitution effects in producing sectors. Table 9.17 shows relative factor intensities in the base case (i.e. present state with undefined property rights). Property rights were defined and the opportunity value of forests (the H-value) was set 28% higher than the value derived from deforestation (Solórzano et al., 1991). The discount rate was 10%. The results are shown in Table 9.18. A comparison of the first and second columns shows that the definition of property rights results in a dramatic decrease in deforestation and an increase in the net import of logs (not shown). Activity in the forest sector increases greatly because logs can be

Table 9.17 Initial capital intensities (percentages) Input

Forest

Land 0 Capital 31.93 Unskilled labour 25.63 Skilled labour 0.43

Agriculture

Industry

14.81 14.68 19.41 0.32

0 11.73 8.25 5.41

Table 9.18 Effect of future valuation on production value (billion colones) Property rights Defined (H-value)a

Undefined Item Deforestation Logging Squatting Total Production Forestry Agriculture Industry Utility Green GDP Disposable income a

0.4792 0.02 0.02 0.04 0.552 13.984 18.477 0.232 31.962 37.681

0 0 0 0.713 13.876 18.416 0.232 31.972 37.679

The H-value is the future value per unit of forest.

0.2792

0.0792

0.002 0 0.002

0.01 0 0.01

0.711 13.876 18.417 0.232 31.971 37.679

0.691 13.879 18.424 0.232 31.971 37.679

300


deforestation cost (billions of colones)

0.0012

0.001

0.0008 squatters loggers

0.0006

0.0004

0.0002

0 0%

10%

20%

30% 40% interest rate

50%

60%

Figure 9.8. Effects of interest rates on the value of deforestation when property rights are well defined.

imported at a constant world market price. The increase in the price of capital is offset by decreases in the price for labour. Deforestation by squatters ceases, and activity in the agricultural sector declines slightly, because land (which is relatively less expensive than capital after the definition of property rights) and labour can be substituted for capital in the sector. The welfare measures remain constant because consumption of different goods is unchanged. Sensitivity analysis (remaining columns in Table 9.18) shows that even a small opportunity value of forests reduces deforestation sharply. However, for deforestation to cease completely, a high value (H = 0.4792) is required. Both the opportunity value of forests and the interest rate are exogenous. Varying the interest rate while keeping the opportunity value fixed shows that high interest rates promote deforestation, and vice versa. The results of varying the interest rate may be deduced from Table 9.18 and Figure 9.8, because decreasing the interest rate is equivalent to increasing the opportunity value, and vice versa. Thus, while deforestation increases with interest rate, the relationship is not linear. Next, the effects of taxes on logs, land, unskilled labour and capital were investigated, as summarized in Table 9.19. A 10% tax increase on logs generated predictable results, with no deforestation from loggers and no production in the forest sector. Resources were shifted to the agricultural sector, with an increase in deforestation for land and an increase in total deforestation. The increase in total deforestation can be explained by the lower price of unskilled labour, resulting from the discontinued production in the forest sector. The tax increase actually results in a higher level of utility, as well as an increase in green GDP. Taxes and subsidies on land generate expected results, with changes in deforestation by squatters and roughly constant deforestation by loggers. Both the tax and the subsidy are


301

Table 9.19 Effects of taxes and subsidies on product factors (billion colones) Logs Item Deforestation Logging Squatting Total Production Forestry Agriculture Industry Utility Green GDP Disposable income

Base case

With tax

Land

With With subsidy tax

Unskilled labour capital



With subsidy

0.02 0.02 0.04

0 0.044 0.044

0.018 0.004 0.023

0.02 0 0.02

0.019 0.255 0.273

0.029 0.21 0.239

0.013 0 0.013

0.036 0.02 0.056

0.011 0.02 0.031

0.552 13.984 18.477 0.232 31.962 37.681

0 14.204 19.248 0.243 32.017 37.748

1.562 13.748 17.017 0.214 31.848 37.561

0.672 13.877 18.430 0.231 31.960 37.678

0 15.122 17.656 0.226 31.757 37.592

0 14.922 17.946 0.229 31.797 37.62

0.689 13.877 18.424 0.232 31.965 37.679

0.515 13.987 18.487 0.232 31.943 37.680

0.574 13.983 18.471 0.233 31.958 37.682

Source: Authors’ calculations.

distortionary and reduce utility as well as income and GDP. When land is taxed, land becomes relatively expensive compared to logs. Then resources are shifted from the agricultural sector to the forest sector, with a corresponding change in production. It is worth noting that the land subsidy dramatically increases deforestation for land, as empirically observed in Costa Rica earlier this century. A 10% tax increase on unskilled labour adversely affects the forest sector and the industry sector, but logging continues and logs are exported. After the tax increase, the price of land is low relative to other production factors, and resources are shifted toward the agricultural sector. The price of unskilled labour in the deforestation sectors is actually reduced, because those sectors are considered to be ‘informal’ in the sense that their activities are, to a large extent, illegal and remain unaffected by government tax policies. Resources are shifted to the agricultural sector, with a large increase in land clearing by squatters as a result. These results also hold for the experiments with capital tax policies, although the magnitude of the changes is smaller. Substitution effects are important when there are tax changes on goods produced in tradables sectors (Table 9.20). Tax changes on goods from the forest sector generate few economy-wide effects because this sector is small compared with the others. The industrial sector (which uses forest products relatively intensively as an intermediate input) gains from the tax reduction and grows, while the forest sector itself suffers. The effects are reversed for a doubling of the tax on forest products. Deforestation remains largely unaffected in both cases. When the tax on agricultural products is reduced to half, the agricultural sector actually decreases, as does the forest sector. This is due to an elevated price of unskilled labour,

302


Table 9.20 Effects of changes in taxes on final products (billion colones) Sector (change relative to original tax rate) Forestry Item Deforestation Logging Squatting Total Production Forestry Agriculture Industry Utility Green GDP Disposable income

Base case

Half

Double

Agriculture Half

Double

Industry Half

Double

0.02 0.02 0.04

0.02 0.02 0.04

0.02 0.02 0.04

0.02 0.019 0.039

0.02 0.022 0.042

0.02 0.018 0.038

0.02 0.025 0.045

0.552 13.984 18.477 0.232 31.962 37.681

0.528 13.984 18.503 0.229 31.941 37.669

0.609 13.985 18.418 0.24 31.98 37.709

0.405 13.258 19.243 0.135 31.589 37.317

0.902 15.706 16.663 0.459 32.815 38.544

0.16 13.964 18.268 0.064 31.324 37.051

1.363 14.03 18.909 0.572 33.253 38.984

Source: Calculations from contributing authors.

which both sectors use relatively intensively. The industrial sector benefits because it uses agricultural products extensively as intermediate inputs, and capital becomes the least expensive production factor. Deforestation for logs remains constant, while deforestation for land is reduced. Utility, income and green GDP are reduced. A double tax on agricultural products generates the opposite effects. A tax on products from the industrial sector generates the same effects as a tax on agricultural products, although the magnitude is larger. A dynamic version of this model, which captures the intertemporal optimization behaviour in the economy, is described in Persson (1994). This is a two-period model, which allows consumers and producers to consider the future effects of policy changes in their decisions in the first period. The opportunity value of forest conservation (the H-value) is endogenous and influenced by relative prices and the size of forests. Further, capital investments are endogenous, as is the domestic interest rate. The qualitative dynamic model confirms the robustness of the results of the static model. Well defined property rights and lower taxes on capital reduce deforestation. 9.7.2 Conclusions The results of the CGE study support the more conventional partial equilibrium approach that establishing property rights tends to decrease deforestation. The reason is that such rights allow forest users to capture the future benefits of reduced logging damage today. Initially, this potentially avoidable loss is presumed to be 28% of the value of the residual stand (Solórzano et al., 1991). Using an interest rate of 10%, the deforestation is dramatically reduced


303

to 5% of the base level as both loggers and squatters internalize deforestation losses and reduce the corresponding activities. Large reductions in deforestation occur even when the estimate of logging damage is substantially reduced. The CGE results concerning the effects of the discount-rate changes parallel the predictions of partial equilibrium models – higher interest rates promote deforestation, while lower interest rates contribute to conservation. The CGE approach also clearly identifies the indirect effects arising from intersectoral linkages. This impact must be combined with the direct effects attributable to policies that are specific to the forest sector to determine the total impact. For example, partial equilibrium analysis predicts that stumpage price increases act directly to reduce logging, yet the model shows that, while deforestation from logging indeed declines, total deforestation nevertheless increases. This phenomenon arises from indirect linkages captured by the general equilibrium analysis. The contraction of the logging and forest industry sectors shifts resources toward agriculture, and, as agriculture expands, deforestation increases. Because of intersectoral resource flows, the CGE captures indirect effects of economywide changes in wages that are different from partial equilibrium results. If wages of unskilled labour were increased (e.g. due to minimum wage legislation), the model predicts that deforestation could worsen instead of decline. Although logging declines due to increased direct costs of higher-wages, this is more than offset by the indirect effect of intersectoral flows because the industrial sector (where minimum-wage legislation is more binding) is much more adversely affected by the higher labour costs. Labour and capital thus tend to flow to agriculture, leading to the conversion of even more forest land for farming. Both the preceding two examples underline the importance of pursuing sectoral reforms in the context of growth. Without alternative employment opportunities, reducing logging activities tends to direct labour and capital resources toward agriculture, industry and other sectors. Expansion of some of these sectors may lead to a second round of effects on forestry, which could ultimately result in more severe deforestation. A dynamic CGE model, in which the value of forest conservation, capital accumulation and the domestic interest rate are endogenized, gives essentially the same results as the static CGE model presented here.

9.8 Appendix A: ECOGEM–Chile CGE model summary 9.8.1 Characteristics of the model The main indices used in the model equations are as follows: i, j l h g f r p

productive sectors or activities types of work or occupational categories household income groups (quintiles) public spending categories final demand spending categories trade partners different types of pollutants

304


Production Production is modelled by the CES/CET nested functions (i.e. constant elasticity of substitution – transformation). If constant returns to scale are assumed, each sector produces while minimizing costs: h i p p p l=i : min PKELi KELi þ PABNDi ABNDi subject to XPi ¼ akel;i KELi i þ aabnd;i ABNDi i Income distribution Production-generated income is allocated in the form of wages, capital returns and taxes among the domestic economy, the government and the domestic and international financial institutions. Consumption Households distribute their income between saving and consumption through an ELES utility function (extended linear expenditure system). This function also incorporates the minimum subsistence consumption independently of the level of income: n X S max U ¼ i lnðCi i Þ þ s ln cpi i¼1 subject to n X i¼1

PCi Ci þ S ¼ YD

and

n X

i þ s ¼ 1;

i¼1

where U is the consumer utility; Ci is the consumption of good i; θ is the subsistence consumption; S is the saving; cpi is the price of savings; and μ is the consumption marginal propensity for each good and to save. Other final demands After defining the intermediate and household demands, the remaining final demands (investment, government spending and trade margin) are included as a fixed share of total final demand. Public finances The following types of taxes and transfers are defined: direct taxation on labour (differentiated by occupational category), taxes on firms and income (differentiated by quintile). We also define import tariffs and subsidies, export taxes and subsidies (by sector), a value added tax (VAT, for domestic and imported goods, by sector) and some specific taxes. As a closure condition for public finances, the model allows two alternatives. First, government spending is defined as fixed and equal to the original level previous to any


305

simulation, allowing it to adjust through some selected tax or government transfer. Alternatively, government spending is allowed to vary, while taxes and transfers are kept fixed. Foreign sector To incorporate the foreign sector, the Armington assumption is used to break down goods by place of origin, allowing imperfect substitution between domestic and imported goods and services. The domestic supply receives a similar treatment, modelled by a CET function to distinguish between domestic market and exports. For imports: min PD XD þ PM XM subject to XA ¼ ½ad XD þ am XM l=l ; where PD and PM are the prices of domestic and imported goods, and XD and XM are the respective amounts; XA stands for the good made up of both or the ‘Armington good’. Parameter ρ is the substitution elasticity between both goods. For exports: l=ll max PD XD þ PE ES subject to XP ¼ d XD þ e ESl ; where PE is the price of the exported good and ES is the respective amount; XP is the sector’s total production. Parameter λ is the substitution elasticity between both goods. Factor market equilibrium conditions To achieve labour market equilibrium, labour supply and demand are made equal for each occupational category, where supply is determined on the basis of real wages. As for the capital market, a single type of capital is assumed, which may or may not have sector mobility depending on the imposed elasticity. Short-term or long-term elasticities could be chosen for the substitution between the factor nest and non-energy-producing inputs, as well as for the CES function between capital-energy and labour, between capital and energy, and for the various energy-producing sectors. Closure conditions The closure condition for the public sector has already been determined. Also, as is usual in such models, the value of the demand for private investment must equal the economy’s net aggregate saving (from firms, households, government and net flows from abroad). The last closing rule refers to balance of payment equilibrium. This equation will be introduced into the model through Walras’ Law.

9.8.2 Reduction of emissions in the model Three options help to reduce polluting emissions: (1) reducing production of highly polluting sectors; (2) changing energy-producing inputs used in the productive process or in consumption

306


(emissions could be reduced by allowing substitution toward less contaminating energy inputs); and (3) introducing ‘end of pipe’ technologies (e.g. filters, treatment plants, etc.). Energy-producing inputs (i.e. coal, petrogas, electricity and gas) are associated with the emission of 13 types of pollutants (not all of them discharged by the energy-producing inputs) through emission factors. These emission factors link the use of each money unit spent in the input with the amount of emissions of each pollutant in physical units. The total volume of emissions in the economy for each type of pollutant is therefore determined by: ! X p X p X X X i Ep ¼ vi XPi þ pi XApij þ XAcih þ XA FDf i

i

j

h

f

that is, by the sum of all the emissions of the pollutant ‘p’ caused by all the productive sectors ‘i,j’ of the input–output matrix (74 sectors for Chile) generated in their productive processes per se, independently of the emissions associated with the use of polluting inputs, in addition to all the emissions derived from the use of polluting intermediate inputs in the productive processes of all the sectors, in their consumption by households ‘h’ and by other components of the final demand ‘f ’. 9.9. Appendix B: Costa Rica CGE model summary 9.9.1 Factor market equilibrium and the stock of forested land K¼

X j2T;N

@ Cj þ klog ; @ PU K

where PKU is the user price of capital and klog is the capital used in deforestation by loggers, and U¼ L¼

X j2T;N

X j2T;N

@ Cj þ lsq þ llog ; @ PU U @ Cj þ lsq þ llog ; @ PU L

where PUU is the user price of unskilled labour, lsq and llog are the labour used in deforestation by squatters and loggers, respectively, and PLU is the user price of skilled labour. Further, d forest ¼

@ forest f nexp ; @ PU F

where dforest is deforestation from the logging sector, PFU is the user price of logs, f nexp is the net export of logs and α is a fixed coefficient reflecting the amount of timber extracted per unit of deforested land. Also, @ Cagric DL d o ¼ 0: @ PU DL where DL* is the stock of cleared land and do is squatter deforestation.


307

The user price, PjU, exceeds the supply price, PjS, by a percentage tax, Tj: S PU j ¼ Pj ð1 þ Tj Þ; j ¼ DLAND; LABOUR; CAPITAL WM PU log ¼ Plog ð1 þ Tlog Þ:

9.9.2 Technology, costs and producer behaviour The gross output in sector j is given by Xj ¼ min

Yj Xij i; j 2 T; N; ; Aj aij

where Yj is a composite input of production factors in sector j, Xij is the input of output from sector i in sector j, and Aj and aij are Leontief input–output coefficients. The marginal and average cost in sector j is given by X PD aij þ tj ; i; j 2 T; N; Cj ¼ PYj Aj þ i i where PYj is the producer price of the composite input of production factors, PiD is the domestic price of sector i output, Aj is the use of production factors per sector j output, aij is the use of sector i input per sector j output and tj is indirect tax per unit of sector j output. We have Pi Ci 0; ðPi Ci Þ Xi ¼ 0;

i 2 T; i 2 T;

Xi ¼ 0; i 2 T; Pi ¼ Ci ; i 2 N:

9.9.3 Prices, domestic demand, foreign trade and market clearing The domestic user price of goods produced in sector i, is given by W PD i ¼ ð1 þ i Þ Pi e ¼ ð1 þ i Þ Pi ;

PD i

¼ ð1 þ i Þ Pi ;

i 2 T;

i 2 N;

where Piw is the world market price of good i, Pi is the producer price of good i, e is the exchange rate and si is the ad valorem tax rate on good i. Further, X Xi ¼ i 2 T; j2T;N aij Xj þ Di þ Zi ; X Xi ¼ i 2 N; j2T;N aij Xj þ Di ; where D is the domestic final demand and Z is the net export.

308


9.9.4 Deforestation sectors Logging sector

dforest ¼ ðklog Þ ðllog Þ ;

þ 51:

Well defined property rights ðl Þ ¼ log

ðklog Þ ¼

log 1=ð1Þ PU U þ@HðdÞ=@ðl Þ ; Plog ðklog Þ !1=ð1Þ log PU U þ@HðdÞ=@ðl Þ : Plog ðllog Þ

Undefined property rights

ðd

log

Þ¼

PU K Plog ðllog Þ

!a=ða1Þ

PU U Plog ðklog Þ

=ð1Þ :

Squatters

do ¼ dðlsq Þ ¼ lsq ; 51; with dð0Þ ¼ 0; dl ðlsq Þ40; dll ðlsq Þ50 and lim dðlsq Þ ¼ B; n!1 where n is the number of squatters, lsq is the labour used in the clearing of the land and B is the total amount of land available for deforestation. I S ðdo Þ ¼ PSDL do ; S where PDL is the supply price of cleared land.

1 o Cs ðdo Þ ¼ Psq L d ðd Þ;

where PLsq is the price of labour in squatting.


HðFÞ 41: 1þi Undefined property rights dio ¼

1 sq dðl Þ; N

where N is the total number of squatters and their total cleared land is given by do ¼

N X

dio ;

i¼1

gs ðdo Þ ¼ I S ðdo Þ C S ðdo Þ; 1 S o g ðd Þ; N 1 PU 1 sq ; l (PDL ; PU) ¼ PDL gSi ðd o Þ ¼

d ¼ o

PU PDL

1

:

Well defined property rights H(do ) ; 1þi 0 1 1 @(H(lsq )=(1 þ i)) 1 B PU þ C @ lsq sq C ; l ¼B @ A PDL gfs (do ) ¼ PSDL d o C S (d o )

1 @(H(lsq )=(1 i)) 1 B PU þ C @ lsq C : do ¼ B @ A PDL 0

Macroeconomic closure X P Z ¼ S; i"T;N i i where S is the current account surplus.

309

310


U U U GNP ¼ PU K K þ PL L þ PU U þ PDL DL þ

X j"T;N

j Xj D(do þ dlog)Hð1Þ;

subject to max U ¼

Q i

Dbi i ; I

P P i

i PD i

bi ¼ 1; Di ¼ 0:

i 2 N; T;

Part IV Sub-national sectoral and system applications

10 Energy-sector applications1

This chapter applies the sustainomics framework to the energy sector. Section 10.1 reviews energy-development issues and status. In Section 10.2, a comprehensive and integrated framework for sustainable energy development (SED) is developed, which identifies practical sustainable energy options by taking into account multiple actors, multiple criteria, multilevel decision making and many impediments and constraints. A case study of Sri Lanka is presented in Sections 10.3 and 10.4, which illustrates application of the SED approach to electricity planning and renewable energy. Both cost–benefit analysis (CBA) and multicriteria analysis (MCA) are used to show how environmental and social externalities may be incorporated into traditional least-cost power system planning. The study is relatively unique in focusing on assessing such concerns at the system level (including technology choices), instead of the more conventional project-level analysis. Sustainable energy policies for Sri Lanka are identified. Section 10.5 describes an SED application in South Africa, using MCA to assess the social, environmental and economic trade-offs arising from policy options relating to electricity supply and household energy use. Finally, Section 10.6 shows that decentralized energy may be more sustainable than centralized generation options for power system expansion in the UK.

10.1 Energy and sustainable development 10.1.1 General background Sustainable energy development (SED) involves the harnessing of energy resources for human use in a manner that makes development more sustainable. Energy production and use have strong links with the economic, social and environmental dimensions of sustainable development. First, economic growth depends on energy services such as heating, refrigeration, cooking, lighting, communications, motive power and electricity. Over two billion people cannot access affordable energy services, impeding their opportunities for economic development and improved living standards. 1 The valuable contributions of P. Meier to this chapter are gratefully acknowledged. Some parts of the chapter are based on material adapted from: Meier and Munasinghe (1994), Munasinghe (1980b, 1990a, 1995b) and Munasinghe and Meier (1993, 2003a).

313

314

Sub-national and system applications

Second, energy is a basic social need that affects human well-being. Wide disparities in access to affordable commercial energy and energy services in both urban and rural areas threaten social stability. Access to decentralized small-scale energy technologies is an important element of successful poverty alleviation. Women and children, who are relatively more dependent on traditional fuels, suffer disproportionately. Third, there are many environmental links (mainly negative), since energy production and use continue to be a primary source of local, transnational and global pollution. Specific impacts include: groundwater and air contamination; land degradation and changes in use; marine and coastal pollution; ecosystems destruction and loss of biodiversity; damage to health, structures and natural systems from SO2 and NOx and ash particulates which degrade air quality; and, finally, greenhouse gas emissions which have harm the global environment (see Chapter 5). Energy for sustainable development will require: the more efficient use of energy, especially at the point of end use in buildings, transportation and production processes; increased reliance on renewable energy sources; and accelerated development and deployment of new energy technologies. Some strategies and policies for globally achieving SED include: encouraging greater international cooperation in areas such as technology procurement, harmonization of environmental taxes and emissions trading, and energy efficiency standards for equipment and products; adopting policies and mechanisms to increase access to energy services through modern fuels and electricity; building capacity among all stakeholders to improve energy decisions; advancing innovation, with balanced emphasis on all steps of the innovation chain; encouraging competitiveness in energy markets to reduce total costs of energy services to end users; cost-based prices, including phasing out all forms of subsidies for fossil fuels and nuclear power and internalizing external environmental and health impacts; encouraging greater energy efficiency; and developing and/or diffusing new technologies to wider markets. Recent trends Economic growth prior to the 1970s was fuelled by increasing energy demand. After 1971, as a direct consequence of passing on the oil price increases to consumers, decoupling between economic growth and energy demand growth was achieved in industrialized countries (ICs). They were able to achieve better energy management by restructuring and through energy-efficient technologies. Such decoupling emerged only later in developing countries (DCs), because energy prices were initially subsidized and kept low for sociopolitical reasons. The current increase in oil prices will continue to curtail demand growth globally. As DCs are still in the early stages of development, and have higher growth rates, there is greater scope for making development more sustainable by delinking economic growth and energy consumption (Munasinghe, 1991). World primary energy demand is projected to expand by more than one-half between 2005 and 2030, or 1.6% annually (IEA, 2005). Over two-thirds of this growth will come from DCs, where per capita use is low. At present, DCs comprise over three-quarters of the world’s population, but utilize only one-quarter of the world’s energy. Most of this population live in rural areas, have little or no access to commercial energy, and rely heavily on traditional biomass fuels such as wood, crop waste and animal dung. The OECD countries, in contrast,

10 Energy-sector applications

315

consume over one-half of the world’s energy and nearly ten times more energy per person than DCs. Per capita use of primary energy in North America was 280 GJ in 2000, over eleven times the Sub-Saharan African value. In OECD Europe and OECD Pacific, per capita energy use was about 142 and 180 GJ, respectively (Goldemberg and Johansson, 2004). Energy demand has been growing rapidly in DCs in recent decades, creating supply shortages. Making energy development more sustainable in the developing world will require reconciliation of economic growth (including increased use of energy) and poverty alleviation efforts, with responsible stewardship of the environment. This has to be done without overburdening already weak economies and without diverting funds from other key goals such as education and healthcare. Energy–economy linkages Modern economies cannot function without commercial energy. Figure 10.1 shows how energy consumption will continue to rise, with fossil fuels such as oil, natural gas and coal playing the dominant role. The major increase will be in DCs, driven by economic expansion, urbanization, the increasing penetration of energy-using products, the transition from traditional energy sources to commercial sources and population growth. The links between total energy use, electricity use and economic output are shown in Figure 10.2. One hopeful trend is that technological progress and efficiency improvements have reduced the energy intensity of economic production (i.e. lower requirements of energy per unit of economic output). Electricity will continue to play an increasingly important social role, as a safe, clean and convenient form of energy. Oil markets As world oil demand continues to grow, it is not surprising that prices are also rising steadily, in anticipation of tightening supplies. This will have serious implications for development, 250

projections

history

quadrillion BTu

200 150

oil

100

coal natural gas

renewables

50

nuclear 0 1980

1990

2003

2015

2030

Figure 10.1. World marketed energy use by type (1980–2030). Sources: International Energy Annual, 2003; EIA (2006).

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Sub-national and system applications 6 energy consumption electricity consumption GDP growth

growth index

5 4 3 2 1

20 20

15 20

10 20

05 20

00 20

95 19

90 19

85 19

19

80

0

year

Figure 10.2. World energy and electricity use and GDP, 1980–2020. Source: Munasinghe (2004d).

especially for poorer oil-importing countries whose growth will suffer, and poor people who cannot afford expensive energy. Internationally, higher oil prices will help to equilibrate markets by curtailing demand growth and stimulating supply. However, the era of cheap and abundant oil appears to be coming to an end, barring an unforeseen (and highly unlikely) new development. The status of oil supplies may be understood by examining the ‘P50’ reserves values, which is an important benchmark used by industry analysts to make assessments (Bentley, 2005). It designates the 50% probable industry estimate for the size of a field’s reserves. P50 estimates correlate well with ‘proved plus probable’ reserves. P50 discovery data and geological estimates suggest that about two-thirds of the world’s oil-producing countries are currently past their resource-limited peak of conventional oil production. According to Chevron, oil production has declined in 33 of the world’s 48 largest oil-producing countries, including the USA, Iran, Libya, Indonesia, the UK and Norway. Others, such as Russia, China and Mexico, will soon go past peak. Figure 10.3 shows how the world has lived off past exploration success, with large finds being drawn down since about 1980 – the historical turning point when global production began to exceed new discoveries. The discovery peak was around 1960, while production may peak during 2005–2015 – based on a Hubbert’s curve type of analysis, which assumes that the future production peak timing is related to the shape and peak of the past discovery curve.

10.1.2 Environmental and social issues Oil- and coal-fired plants not only have national impacts, but also regional and global environmental and health effects. Electricity is an important form of energy, which has relatively few environmental and health consequences at the point of end use, but key


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70 60 avg. discovery Gb/year

50 40 30 20 10 0 1900

production 1920

1940

1960

1980

2000

Figure 10.3. ‘P50’ discovery and production of oil and non-gas liquids during 1900–2000, in gigabarrels (Gb) per year. Source: IHS Energy. The discovered oil totals 2033 Gb; the produced oil is 46% of this (934 Gb).

environmental and social issues arise from power generation. Even sources like hydro, solar and wind power, geothermal energy and ocean energy, which are perceived to be ‘clean’, have some negative impacts on the surroundings. National issues – conventional energy Fossil-fired plants Currently 65% of the world’s commercial energy is produced from fossil fuels – oil (7.7%), coal (39.5%) and natural gas (18.2%) (EIA, 2005). In the case of oil- and coal-fired plants, major public health risks arise from emissions of sulphur dioxide, carbon monoxide, nitrogen oxides, hydrocarbons, polycyclic organic matter and additional pollutants from coal, such as fly ash, trace metals and radionuclides. Exposure to these pollutants leads to increased incidence of respiratory disease, toxicity and cancer. Disposal of solid waste leads to health risks associated with leaching and groundwater contamination. Natural gas-fired plants pose a public health risk from nitrogen oxides and particulate emissions, but are significantly less hazardous to health in comparison with oil- or coal-fired plants. Coal mining, transportation and washing also have substantial adverse impacts on environment. Fuel oil emits 85–90% as much carbon dioxide as coal, and natural gas under 60% for the same thermal content. Without treatment or control, coal emits more particulate matter (PM), sulphur dioxide and nitrogen oxides than any other fuel. While PM emissions from oil and gas are negligible, coal emits almost 10% of its oil equivalent in weight as ash and other matter. Sulphur dioxide emissions depend on sulphur content of the fuels, while emissions of nitrogen oxides are not significantly different between fuels, with gas emitting only two-thirds that of coal. Nuclear plants Nuclear fission reactors currently produce over 15% of electricity worldwide and were intended to replace fossil-fuelled capacity in the medium-term (EIA, 2005). Safety concerns, driven by

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accidents at Three Mile Island and Chernobyl, have made nuclear energy politically and economically unattractive. However, in a few countries like France and Japan, nuclear reactors are used extensively. Though nuclear energy does not emit atmospheric pollutants like fossilfuel technologies, the fission reaction generates long-lived, highly radioactive wastes whose ultimate disposal is extremely controversial. Nuclear power also causes groundwater contamination. It is more capital intensive than fossil-fuel power generation, and costs are controversial. Occupational health risks, which may have intergenerational consequences, arise from exposure to radiation. Public health risks result from low-level radiation from power production and waste disposal. High exposure to radiation is possible in the event of major accidents, with potential long-term health implications. While actual public risk may be relatively small, public fears of risks from nuclear plants and waste disposal sites are extremely strong and cannot be dismissed (often based on risk-averse reactions to potentially catastrophic, though rare, accidents). Hydroelectricity Almost 7% of worldwide electricity is produced from large hydroelectric dams that utilize reservoirs or waterfalls – see Section 6.4 for details. National issues – new and renewable energy In 2002, biomass, wind and geothermal were the major contributors among new and renewable energy sources (excluding hydroelectricity). A six-fold increase is projected by 2030 (see Sections 15.4 and 10.2.3). Small hydro Mini- and microhydro plants are popular for providing local power supply and irrigation without the massive environmental and social impacts arising from large hydro schemes. Microhydro-projects are currently underway in many DCs, which have the advantage of providing electricity to rural areas beyond the central grid (Munasinghe, 1987). Solar energy Advances in solar thermal technologies and direct electricity generation by photovoltaics (PVs) have reduced costs significantly since the late 1990s.2 While these techniques pose no significant occupational and health risks at the generation stage, some environmental impacts may arise from the loss of land use resulting from its high land intensity. Solar energy is constrained by its limited applicability. Geothermal energy Geothermal energy uses the Earth’s heat to drive steam turbines. Cost-competitive exploitation of geothermal energy with current technology is largely limited to the volcanically active Pacific ‘Ring of Fire’ and the Mediterranean, where suitable steam reservoirs are 2

Private communication: RE Focus (2005), ‘Prospects for solar energy’, pp. 25–9.


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located within one mile of the surface. Geothermal steam carries with it a number of atmospheric pollutants, including carbon dioxide, mercury and radon. Currently, the toxins are commonly re-injected into the reservoir. With recent advances, hot dry rock technology will be competitive with conventional geothermal technology and fossil-fuelled plants. Biomass power generation A wide range of options exists for converting biomass into electric power. Dendro-thermal power plants use boilers to burn wood from fast-growing species (grown on dedicated plantations) to generate electricity through a conventional steam cycle. Most potential applications are for remote power supply in DCs. Concerns about the effects of dedicated fuelwood plantations on the local environment and competing land uses impose constraints on the widespread adoption of dendro-thermal power supply schemes. It is economical to use biomass for energy purposes only where it is available as a byproduct of other processes. Another source of biomass for power generation is municipal solid waste, whose use is limited both by public concern over emissions and the shortage of concentrated sources of solid waste. In tropical areas, the water content of solid wastes reduces its attractiveness as a fuel. Wind power Large grid-connected wind generators (75 kW–450 kW) in multiturbine ‘wind farms’ now supplement power grids in many countries. The total installed wind-power capacity was about 47 300 MW in 2004, with Germany, Spain and the USA accounting for 35%, 18% and 14%, respectively (MIT, 2005). However, wind energy provided only 0.3% of the total electricity supply. Research is underway on combined wind- and gas-turbine power supply schemes that would provide reliable power on demand, at minimal cost. Although wind generators do not produce air or water emissions, the larger turbines on the landscape are visually and aesthetically unappealing, emit acoustic noise, generate electromagnetic interference and present a hazard to birds. Ocean energy Pilot plant experience with ocean thermal energy conversion (OTEC) indicates that temperature differences of 20°C between surface waters and waters about 1000 m below are sufficient for economic power generation. There is a vast potential for this energy source in the tropical oceans. Due to high capital requirements and the unproven technology, no large commercial plants are functioning. Environmental concerns include effects on sea life and the atmospheric release of carbon dioxide stored in deep ocean waters. Conversion of wave energy into electricity is also in the R&D stage, although some commercial power plants (e.g. tidal power stations) are in operation. Impacts on marine organisms, shipping and fishing are potential concerns. Transnational and global issues Acid deposition is a serious transnational issue, resulting from oxides of sulphur and nitrogen emitted by fossil-fuel plants, falling to the ground as particulates and acid rain.

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The transport of sulphur dioxide occurs over long distances (greater than 1000 km). Acid rain, caused by sulphur and nitrogen oxides, results in damage to vegetation and leads to acidification of streams and lakes, resulting in the destruction of aquatic ecosystems. They also cause corrosion, erosion and discoloration of buildings, monuments and bridges. Indirect effects on human health are caused by the concentration of heavy metals in acidified water and soil (USEPA, 2004). Other important transnational issues include environmental and health impacts of radiation due to severe nuclear accidents (Chernobyl); oceanic and coastal pollution due to oil spills (Amico Cadiz, Exxon Valdez and the Braer); downstream siltation of river water in one nation, due to deforestation of water sheds and soil erosion in a neighbouring country; and changes in hydrological flow and water conditions caused by dams. Climate-change impacts due to greenhouse gas emissions are set out in Chapter 5.

10.1.3 Power-sector role and issues Electricity is clean, versatile, easily accessible and simple to distribute. It is also essential to maintain a reasonable quality of life and for sustainable development. Thus, world electricity demand is increasing at over 1.5 times the growth rate of demand for primary energy. By 2040–2050, more than half the world’s primary commercial energy sources would be utilized in electricity production. Electricity in developing countries Although electricity is essential to modern economies, over two billion people are without access to it. The industrialized countries contain about 15% of the world population, while consuming almost 60% of the globe’s electricity. In DCs, per capita energy consumption is between onethird and one-fifteenth of industrialized countries (UN, 2006). While per capita energy and electricity consumption are generally correlated with per capita income (Figure 10.2), Europe and Japan are considerably less energy intensive than the USA. Meeting basic electricity needs (1 kWh per family per day) requires 60 GW more of generation, or less than 2% of currently installed global capacity. The cost of providing this additional power is about EUR 180 billion, or slightly over EUR 7 billion per year over 25 years (GENI, 2004). Worldwide electricity revenues were over EUR 800 billion in 2000. It is necessary also to supply population due to demographic growth of about 1.5% per year, or an additional one billion people up to 2030. Electricity greatly enhances the quality of life in DCs, improving the health, education and productivity of the poor. Rural electrification (RE) also helps to retard migration from rural areas to cities and enhances opportunities for sustainable livelihoods. Electricity demand in DCs grew at 10% and 8% in the 1970s and 1980s, respectively, but declined to 6–7% in the 1990s and 2000s. World electricity consumption will double between 2003 and 2030, with non-OECD and OECD countries, respectively, accounting for 71% and 21% of this growth (EIA, 2006). The Asia Region (mainly China and India) dominates with almost two-thirds of the non-OECD total, and coal and hydro are the primary sources.


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Power-sector problems Electricity demand in many DCs has exceeded their power-generating capacities, resulting in frequent power shortages. Power cuts handicap productive activities and delay social development. On the output side, electricity shortages disrupt production. For example, power cuts in Sri Lanka during 1996 and 2001–2002 were estimated to have cost 1–2% of GDP (Munasinghe, 2003). Power shortages also restrict investment and employment – hindering production and requiring more costly investment for on-site electricity production or standby supplies (Munasinghe, 1990b). Structural, institutional and financial problems further exacerbate electricity supply in DCs. Poor operating performances and maintenance of plants, high transmission and distribution system losses and high fuel consumption have resulted in unsustainable energy wastage and economic losses. The availability of generating capacity is below 60% for thermal plants in DCs, compared with over 80% in developed countries (World Bank, 1994a). Power plants in DCs consume 15–30% more fuel per unit of electricity than those in ICs (WRI, 1994). Transmission and distribution system losses in DCs cost over $30 billion. Inadequate tariffs due to governmental policies and poor revenue collection due to inadequate metering, as well as poor accounting and billing, have led to large financial losses and difficulties in raising investment capital. While institution building has continued to progress, conflicts between governments’ role as owner, and its role as operator of utilities, have affected sector performance. Opaque command and control management, poorly defined objectives, government interference in daily affairs and lack of financial autonomy have undermined institutional performance. To meet growth in electricity demand, DCs will require several hundred billion US dollars per annum to finance future capital investments. Local capital is inadequate to meet these needs. Despite power-sector reform and privatization programmes encouraged by the donors, there is growing resistance in many DCs to selling off public assets in key sectors to private (mainly foreign) owners and skepticism about the ‘benefits’ claimed by privatization advocates. Furthermore, private investors are reluctant to re-enter DCs that continue to experience difficulties in servicing their foreign debt. Further, future power-sector expansion in DCs will have serious environmental impacts. 10.2 Framework for sustainable energy development The sustainomics approach leads us to a comprehensive and integrated conceptual framework for energy-related decision making (Munasinghe, 1995b, 2002b). Najam and Cleveland (2003) identify three key energy–sustainable development links: (a) driving economic growth; (b) meeting basic human needs; and (c) stressing the environment – corresponding to the economic, social and environmental dimensions of the sustainable development triangle. Power and energy planning must be part of, and closely integrated with, overall development planning and policy analysis to meet many specific, interrelated and frequently conflicting national objectives. Specific goals might include: (a) ensuring economic efficiency in the supply and use of all forms of energy, to maximize growth – other energy efficiency-related

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objectives are energy conservation and elimination of wasteful consumption, and saving scarce foreign exchange; (b) raising sufficient revenues from energy sales, to finance sector development; (c) addressing social concerns like basic energy needs of the poor, sustainable livelihoods and equity; (d) ensuring an adequate quality of energy supply; (e) diversifying supply, reducing dependence on foreign sources and meeting national security requirements; (f) contributing to development of special regions (particularly rural or remote areas) and priority sectors of the economy; (g) price stability; (h) preserving the environment, etc.

10.2.1 Integrated approach Figure 10.4 summarizes a hierarchical decision making framework for sustainable energy development (SED) that takes into account multiple actors, multiple criteria, multilevel decision making and constraints. It may be implemented through a set of energy supply and demand management policy options. The core of the SED framework is the multilevel analysis for integrated national energy planning (INEP) shown in the middle column (Munasinghe, 1980b, 1988). At the global level, there are exogenous constraints imposed on countries. The next hierarchical level focuses on links between the energy sector and the multisectoral national economy. Energy planning requires analysis of the energy needs of user sectors (like industry and transport), the input needs of the energy sector and the impact on the economy of policies

international institutions

multiple criteria

integrated multilevel analytical framework

economic efficiency

multinational corporations international NGOs

social equity

banks government institutions R&D institutions energy utilities consumers public interest groups local NGOs

financial viability

environmental sustainability

other

economic, environmental and social assessments and interactions

multiple actors

country A

global/transnational level (international interactions) country I

country H

national macroeconomic level (interactions between energy sector and other sectors) agriindustry transport energy water health other culture

sub-national energy-sector level (interactions within the energy sector) new and electric gas oil coal fuelwood renewable power

impediments

international finance technology transfer treaties and protocols guidelines

uncertainties (costs, technology development, environmental impacts, etc.) lack of analytical tools

laws regulations guidelines R&D economic instruments (including price)

demand management

lack of infrastructure and skilled man power weak institutions inadequate funding

other

electric power sub-sector/project level (sub-sector planning and management) supply management

policy instruments

timely plans plant requirements (siting, licensing, technology, etc.) public participation

lack of public comprehension and consistent political will

decision making process to determine sustainable energy development path

Figure 10.4. Sustainable energy development framework. Source: adapted from Munasinghe (1980b).


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concerning energy prices and availability. The intermediate level of SED permits detailed analysis, with special emphasis on interactions among the different energy sub-sectors (like electricity and oil), substitution possibilities and resolution of any resulting policy conflicts. The lowest level focuses on individual energy sub-sectors, especially project planning and implementation. Social and environmental interactions (vertical bar) cut across all levels. SED facilitates policy making and does not imply rigid centralized planning. Thus, such a process should result in the development of a flexible and constantly updated energy strategy designed to meet national sustainable development goals. This sustainable energy strategy may be implemented through energy supply and demand management options that make effective use of decentralized market forces and incentives. Figure 10.4 shows a variety of policy instruments for sound energy management. SED also considers the interests of multiple actors, ranging from international institutions to local energy users. The figure also indicates the most important impediments that limit effective policy formulation and implementation. Sustainable energy options: ‘win–win’ outcomes versus trade-offs Sustainable energy options that lead to improvements in economic, social and environmental are called ‘win–win’ options. Once ‘win–win’ cases are identified, trade-off situations may be addressed as set out in Section 3.5. Environmental and social impacts need to be valued in economic terms and introduced into conventional CBA. When such valuation is difficult, MCA may be used. Better energy management could lead to improvements in economic efficiency (more net output produced with given resources), energy efficiency (higher value of net output per unit of energy used), energy conservation (reduced absolute amount of energy used), environmental protection (reduced energy-related environmental costs) and social benefits (more accessible energy). However, it may not always be possible to satisfy all the above goals simultaneously. The economic efficiency criterion, which maximizes the value of the net output from all scarce resources (including energy), effectively subsumes purely energyoriented objectives such as energy efficiency and energy conservation. Key sustainable energy options are discussed below.

10.2.2 Improving energy efficiency Improving energy efficiency (by obtaining more light, heat and mobility from less energy) is usually a win–win option. It lowers investment and fuel costs, and increases business profits and consumer welfare, while reducing environmental harm and enhancing social benefits. However, the demand stimulated by subsequent reduction of energy costs, new uses of energy and population growth often expands energy use. During the past century, despite an over tenfold improvement in energy efficiency, world commercial energy use also increased tenfold. The total final energy consumption per unit of GDP (TFC/GDP) in OECD countries fell 38% during 1973–1999. The IEA (2000a) projects TFC/GDP to decline over the next two decades by 1.0% a year in OECD countries, compared with the annual 1.2% decline registered between 1973 and 1999. Global TFC/GDP is projected to decrease by about

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1.1% a year, compared with the annual rate of 0.9% during 1973–1999. The carbon intensity of world economic product dropped by more than 20% during 1970–1986, and 75% of this was achieved due to energy efficiency gains. In 1990, OECD countries were able to produce a unit of economic output using little more than half the energy required by non-OECD countries. Energy efficiency may be improved via supply and end-use options. Supply side improvements Short-term supply efficiency enhancing technological options for the DC power sector include improving transmission and distribution losses and generation plant efficiencies. They yield net economic savings that are several times the corresponding costs incurred (Munasinghe, 1990b). Total energy losses in DC power systems are estimated to average in the 16 to 18% range. The average system losses in South Asia have been estimated at 17% and in East Asia at 13% (Munasinghe, 1991). Older power plants in many DCs consume 18 to 44% more fuel per kWh produced than those in OECD countries, and utilities suffer line losses that are two to four times higher (Levine et al., 1991). Gas-fired combined-cycle gas turbine (CCGT) plants offer high efficiency (up to 60%) combined with the low carbon content of natural gas, producing electricity with less than half the carbon emissions of coal-fired plants. Basic pulverized fuel (PF) coal technologies can achieve efficiencies of about 45–50%, and other advanced technologies are approaching commercial viability. Efficient transformer technology can generate major energy savings, typically 100–150 TWh/year of electricity in OECD countries (over 70 million tonnes of CO2). Large-scale inexpensive electricity storage can lead to more efficient use and distribution of energy, can accelerate renewables use and it can lower liquid-vehicle-fuel use. Green house gas (GHG) emissions may be reduced with carbon-free technologies and CO2 capture and sequestration. Overall, there is need for enhanced reliability, robustness and resilience of energy service networks, including system integration in energy supply, delivery and use. Demand side improvements Energy-efficient demand side management (DSM) programmes include the planning, implementing and monitoring activities of electric utilities, to encourage consumers to modify their level and pattern of electricity usage. These technologies could promote more efficient lighting, heating and cooling in the developing world. DSM will help to balance electricity supply and demand, stabilize prices, raise system reliability and security, rationalize investment in electricity supply infrastructure and reduce GHG emissions. Traditionally, DSM was used by electric utilities as a load and investment management tool, within a ‘least-cost planning’ framework. DSM is now finding new applications as a market-based service in liberalized energy markets (IEA, 2006). Since major demand growth in DCs will continue, and technologies and appliances are generally based on old designs, gains in overall electricity system efficiency are possible from DSM. Policies to encourage cost-effective, energy-efficient technologies include (IEA, 2000b): (1) energy information, technical assistance and equipment labels; (2) regulations and


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Table 10.1 Key energy-efficient technologies and practices Building envelope Space conditioning

Appliances Cooking Lighting

Motors Other

energy-efficient windows, insulation (walls, roof, floor), reduced air infiltration air conditioner efficiency measures (e.g. thermal insulation, improved heat exchangers, advanced refrigerants, more efficient motors), centrifugal compressors, efficient fans and pumps and variable air volume systems for large commercial buildings advanced compressors, evacuated panel insulation (refrigerators), higher spin speeds in washing machines/dryers improved efficiency biomass stoves, efficient gas stoves compact fluorescent lamps, improved phosphors, solid-state electronic ballast technology, advanced lighting control systems (including day lighting and occupancy sensors), task lighting variable-speed drives, size optimization, improving power quality building energy management systems, passive solar use (building design), solar water heaters

standards for products and practices; (3) economic instruments, especially prices; (4) voluntary agreements (VAs) between industry and government; (5) energy research, development and dissemination (RD&D); and (6) public infrastructure planning and construction. Table 10.1 shows key DSM methods that reduce electricity use, local environmental and social impacts and GHG emissions. One major reason DCs hesitate to adopt these technologies is their fear of high costs. However, when all the system-wide costs are included, energy-efficient equipment often provides the same energy services at a lower installed capital cost than less efficient equipment (IEA, 2006). Unfortunately, potential buyers of new energy-efficient devices may still be unable to buy them because they do not have the necessary funds or access to credit facilities.

10.2.3 Implementing environmentally and socially benign options As they expand energy supply to meet rapidly rising demand, DCs will look to industrialized nations to provide leadership in refining and testing new technologies before adopting them. In particular, renewable-energy sources and fuel switching are two important socially and environmentally benign technologies (Bryne, Toly and Glover, 2006). Renewable-energy sources Around 17% of the world’s primary energy is supplied by renewable sources, including traditional biomass, large hydropower and ‘new’ renewables (small hydro, modern biomass, wind, solar, geothermal and biofuels). Traditional biomass, primarily for cooking and heating, represents about 9% and is growing slowly or even declining in some regions as biomass is used more efficiently or replaced by more modern energy forms. Large

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hydropower is about 6% and growing slowly, mainly in DCs. New renewables are 2% and growing very rapidly in ICs and in some DCs (REN21, 2005); see also Section 15.4. Renewable energy has not made as much progress as expected in the past 20 years. In the OECD, the share of renewable energy in total primary energy has declined (Jefferson, 2005). The worldwide share of coal has increased since 2000, and that of large hydro and nuclear have decreased. In 2004, renewable power capacity (excluding large hydropower) totalled 160 GW worldwide, or about 4% of power-sector capacity. Small hydro and wind power accounted for two-thirds of this capacity; DCs had 70 GW. Renewable energy generated as much electricity as one-fifth of the world’s nuclear power plants. During 2000–2004, electricity production from solar photovoltaic systems, as well as grid-connected wind turbines, has grown at about 30% per year, and geothermal and solar thermal heat production have grown about 10% per year (Goldemberg and Johansson, 2004). In developing countries, 16 million households use biogas for cooking and lighting, while over two million homes use solar PVs for lighting. The fastest growing energy technology in the world has been grid-connected solar PVs, with a total existing capacity increasing from 0.16 GW in 2000 to 1.8 GW by 2005 – a 60% average annual growth rate. Between 2000 and 2004, renewable-energy technologies grew rapidly (annual average): wind power 28%; biodiesel 25%; solar hot water/heating 17%; off-grid solar PVs 17%; geothermal heat capacity 13%; and ethanol 11%. Other renewable-energy power-generation technologies, including biomass, geothermal and small hydro, are more mature and growing at more traditional rates of 2–4% per year. These growth rates compare with annual growth rates of fossil-fuel-based electric power capacity of 3–4%, a 2% annual growth rate for large hydropower, and a 1.6% annual growth rate for nuclear capacity during 2000–2002. Large hydropower remains one of the lowest-cost energy technologies, although environmental constraints, resettlement impacts and the availability of sites have limited further growth (see Section 6.4). It supplied 16% of global electricity production in 2004, down from 19% a decade ago. Large hydro totalled about 720 GW worldwide in 2004 and has grown historically at slightly more than 2% per year (half that rate in developed countries). Small hydropower has developed worldwide for more than a century. Over half the world’s small hydropower capacity exists in China – nearly 4 GW of capacity was added in 2004 alone. Wind power has grown from a miniscule 1930 MW in 1990 to more than 47 317 MW in 2005. Especially noteworthy is the rapid growth of wind power in Denmark (35% per year since 1997), Spain (30% per year since 1997) and Germany (68% per year since 2000). Wind now generates more than 20% of Denmark’s electricity. About 600 MW of offshore wind exists, all in Europe. Brown (2004) suggests that offshore wind alone might produce all of Europe’s residential electricity. Nevertheless, it faces challenges for truly large-scale deployment. Public resistance in visible locations is growing, shifting the emphasis to over-thehorizon, off-shore wind platforms. The price of wind-generated electricity has declined sharply, from $0.46/kWh in 1980 to $0.03–$0.07/kWh in 2003 (Sawin, 2004). Brown (2003) notes that wind satisfies equally weighted economic, social and environmental criteria. Biomass electricity and heat production is slowly expanding in Europe; e.g. in Sweden, biomass supplies more than 50% of district heating needs. Among DCs, small-scale power


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and heat production from agricultural waste is common, for example from rice or coconut husks. Sugar cane waste (bagasse) is used for power and heat production in countries with a large sugar industry. Modern biomass can be economically produced in rural areas, with minimal, or even positive, environmental impacts through perennial crops. Its production and use is helping to create international bio-energy markets, stimulated by policies to reduce carbon dioxide emissions. Geothermal heating is used in 76 countries and geothermal electricity in 24 countries. Over 1 GW of geothermal power was added between 2000 and 2004. Geothermal direct-heat utilization capacity nearly doubled from 2000 to 2005, an increase of 13 GW. Iceland leads the world, supplying 85% of its total space-heating needs from geothermal. Grid-connected solar PV installations are concentrated in three countries: Japan, Germany and the USA, with over 400 000 homes using rooftop solar PVs feeding power into the grid. This market grew by about 0.7 GW in 2004, from 1.1 GW to 1.8 GW cumulative installed capacity. Solar hot water/heating technologies are becoming widespread, with China accounting for 60% of total capacity worldwide (REN21, 2005). Despite steady declines in the cost per kWh of energy generated by PV cells, this alternative remains a costly solution by conventional standards. Moreover, the technology does not appear to have significant scale economies, partly because the efficiency of PVs cannot be improved by increasing the size of the device or its application. Solar PVs (and other small-scale electricity generation technologies) can overcome social barriers through a combination of clean energy, microfinance and community empowerment. Biofuel production of 33 billion litres in 2004 compares with about 1200 billion litres annually of petrol production worldwide. Brazil has been the world’s leading user of fuel ethanol for more than 25 years, producing about 15 billion litres in 2004, exporting a further 2.5 billion litres (more than half the global trade). The future global share of renewables in energy use is projected to decline from 14% in 1997 to 12% in 2020. The world is expected to use 50% more hydroelectricity by 2020, mainly in DCs. The biggest increase in renewable-energy use is expected to come from wind and bioenergy, which are supported by policies and measures to curb GHGs and to diversify the energy mix. Despite this strong growth, the share of non-hydro renewable energy in the global energy mix will reach only 3% by 2020 because of the current low starting point of 2%. Future renewable-energy use in DCs (including hydro and ‘non-commercial’ combustible renewables and waste) will increase by 35% (IEA, 2006). Yet, their share of total DC energy demand will decline from 26% in 1997 to 18% in 2020. These baseline projections could change with the adoption of new policies. In summary, non-conventional sources can help to meet energy needs in an efficient and cost-effective manner, particularly in DCs, where most of the growth in demand will occur. Hall et al. (2003) argue that subsidies and externalities have tilted the playing field toward hydrocarbons, which underlines the need for public-policy intervention that would encourage the research, development and adoption of renewable forms of energy, to make development more sustainable. Significant barriers will hamper renewable-energy development, unless action is taken by governments, the private sector and individual energy consumers to overcome risks,

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high costs, regulatory obstacles, limited availability of products, lack of public acceptance, information and technology gaps, lack of infrastructure and inadequate incentives. Fuel switching The substitution of primary energy sources in power generation is an important potential means of achieving dual benefits. In the case of substituting natural gas for coal or oil, the economic benefit comes from either import substitution for petroleum products or releasing these products for export. Further, natural gas firing typically achieves a 30–50% reduction in carbon emissions. Major reductions in polluting sulphate emissions can be achieved by substituting low sulphur coal or other fuels for low-grade coal. Investing in gas- and oil-fired power plants would also reduce carbon dioxide emissions, although this may increase dependence on expensive oil or gas imports. Time lags are important. Historical experience suggests that, even with strong incentives, roughly 15 years are needed to switch from older production processes (e.g. in steel making) to newer ones, throughout a national industrial sector. Major fuel switches in energy systems have taken up to 20 years.

10.2.4 Institutional and regulatory reform Over the twentieth century, many vertically integrated power companies, both state and privately owned, have emerged around the world. Michaels (2005) claims that such companies offer significant cost savings. While the State-Owned Enterprise (SOE) model makes more sense for a smallish country with a weak private sector, it suffers from several shortcomings. Excessive government interference in organizational and operational matters has been a major problem in many parts of the developing world. This has adversely affected least-cost procurement and investment decisions, hampered attempts to raise prices to efficient levels, mandated low salaries and promoted excessive staffing. This in turn has resulted in inadequate management, the loss of experienced staff due to uncompetitive employment conditions and poor job satisfaction, weak planning and demand forecasting, inefficient operation and maintenance, high losses and poor financial monitoring, controls and revenue collection. Incentives for utility managers to pursue technical efficiency and financial discipline, to minimize consistently production costs and to provide reliable services are lacking in DCs. Lack of internal funding, together with poor planning, operation and maintenance practices has resulted in a widespread maintenance backlog and poor availability of generation capacity in DCs, thereby increasing the pressure for new generation. In some countries, state-owned power monopolies have grown to become a virtual mini-government, hardly accountable to anyone. There is little pressure to improve customer service or engage in technological innovation. With scant financial scrutiny, such SOEs tend to underperform. In many DCs, central governments do not have sufficient resources to invest adequately in infrastructure, resulting in chronic power shortages and poor service reliability (Sioshansi, 2006).


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The natural monopoly characteristics of some power enterprise functions, and the necessity to manipulate these enterprises for general policy purposes, have been cited as reasons for maintaining large centralized public-sector organizations. Nevertheless, given the observed problems inherent in stimulating management of these enterprises to be cost conscious, innovative and responsive to consumer needs, there may be a need for more fundamental change. It could be worthwhile to trade off some of the perceived economies of scale in energy enterprises for other organizational structures, which provide greater built-in incentives for management efficiency and responsiveness to consumers. Political decision makers, senior government officials and ministry-level staff should focus on critical macroeconomic and energy-sector strategy and policy. The senior management of a power company, appropriately guided and buffered by an independent board of directors, would then conduct their daily operations free from government interference to meet the overall national policy objectives and targets within regulatory guidelines. As far as possible, the utility management should be assured of continuity at the top, even in the face of political changes. While the enterprise enjoys wider autonomy, it would become more accountable in terms of performance measured against an agreed set of specific objectives and monitored indicators. Managerial training and education for staff are critical to ensure the success of such an approach. There is considerable interest in the scope for more decentralization and greater private participation. DC power sector officials have been very active in studying such options, and some countries have already prepared the necessary legislative and institutional groundwork for this transition. In some countries, reform initiatives have begun, including divestiture of SOEs and encouragement of private power schemes. Options for private and cooperative ownership of energy enterprises could include both local and foreign participation as well as joint ventures. As long as a given regulatory framework prevails, it can be argued that the form of ownership (private and public) would not by itself affect operating efficiency. A first step toward decentralization could be for government-owned power enterprises competitively to contract out activities or functions better handled by others, such as billing and collection process or routine maintenance. Among the advantages of such arrangements are lower costs and greater programming flexibility. In the regulated monopoly model, the private sector owns and operates significant components of infrastructure, usually supervized by an independent regulator. This model offers a number of advantages relative to the centrally planned SOEs, such as the presence of an independent regulator, which should be competent, resourceful and vigilant. It offers the opportunity to capture the significant economies of scale of large vertically integrated monopolies while controlling their abusive tendencies. Another advantage is that the financial pressure exerted on privately owned monopolies is not as intense as it would be if they were private and non-regulated. Regulated monopolies are generally considered both low-risk and low-return. Although private investors finance projects and bear some risk, captive customers assume most of the risks through the regulatory review and approval process (Newberry, 2005).

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There are also opportunities for spatial decentralization. For example, larger countries may have independent regional power grids. Power distribution companies could be separate by municipality, with perhaps limited overlap in fringe franchise areas, and have the right to purchase from various suppliers. If private participation were allowed, one advantage might be that at least the large power consumers could also be legitimate shareholders who would be concerned not only with service efficiency, but also with the financial viability of the company. Power generation also has potential for efficiency improvements through divestiture. While the bulk power transmission and distribution functions might be regarded as having more natural monopoly common-carrier type characteristics, this is not so with generation. In fact, there is substantial scope for competition in power generation, with independent producers selling to a central grid (e.g. large industrial co-generation). Free-standing generation companies would put up all or part of the capital and be paid only out of revenues from power sold at guaranteed prices. This would reduce the emphasis on large, lumpy capital-intensive projects. In theory, opening electricity markets could lead not only to lower prices in the short run, but also to innovations in technology and marketing plans with more substantial benefits. However, making electricity markets more competitive is complicated by an inability to approach the market ideal of perfect competition (see Box 2.3). For example, the local distribution of electricity is a monopoly because it would be wasteful for a second provider to install its own lines, poles and conduits over the existing grid. Until customers can economically produce electricity on their own premises using ‘distributed-generation’ technologies, local distribution and long-distance transmission will need to remain regulated monopolies. The disastrous experience of California during the 1990s shows the pitfalls of energy reforms without adequate forethought (Brennan, 2001). In 1996, California loosened controls on its energy markets and increased competition. Deregulation involved partial divestiture of electricity generation stations by the utilities, who were still responsible for electricity distribution and were competing with independents in the retail market. A total of 40% of the installed generating capacity was sold to ‘independent power producers’. By 2000, wholesale prices were fully deregulated, but retail prices were still regulated. After June 2000, bulk electricity prices skyrocketed, and reserves hit precariously low levels, resulting in blackouts. Incumbent utility companies incurred huge losses as they were forced to purchase wholesale power at high (unregulated) prices and sell at lower (regulated) retail prices. This allowed independent producers to manipulate prices by withholding electricity generation, arbitraging the price between internal generation and imported (interstate) power, thus causing artificial transmission constraints. The incumbents (still subject to retail price caps) were faced with unabated end-user demand, while supply was restricted. Electricity and gas markets also interacted to produce erratic price movements that confused both energy producers and users. The dramatic collapse of Enron and the ensuing financial scandals were also closely linked to this process. Opponents of deregulation were quick to point out that the fully regulated system had


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worked perfectly well for 40 years, and that hasty deregulation created an opportunity for unscrupulous speculators to wreck a viable system. Pro-privatization advocates insist that the regulator overcontrolled and stifled the market. Beyond this debate, the California example (and others) show that DCs with fledgling market mechanisms and weak regulation must exercise caution before undertaking drastic sector reforms. In a comprehensive recent review, Joskow (2006) states that ‘the transition to competitive electricity markets has been a difficult process in the US’. He indicates that the results have been mixed, with no clear winner thus far between the half of the country, which is dominated by traditional regulated monopolies, and the other half, which is promoting privatization and competitive markets. To sum up, while the traditional model of large, monolithic, vertically integrated monopolies has major shortcomings, the transition to the other extreme of a fully privatised energy sector also poses significant risks (Griffin and Puller, 2005). Decision makers are searching for country-specific reform paths that strike the appropriate balance.

10.2.5 Sustainable energy pricing policy This section briefly reviews how the principles of sustainomics may be used to frame a sustainable energy pricing policy. Further details are provided in Chapter 14, in the context of integrated energy pricing, and especially electricity pricing policy. Sustainable energy pricing policy as applied to the electricity sector needs to incorporate economic efficiency, as well as social equity and environmental considerations. In the past, the electric-power pricing policy in most countries was determined mainly on the basis of financial or accounting criteria – e.g. raising sufficient sales revenues to meet operating expenses and debt service requirements, while providing a reasonable contribution toward capital needed for future power-system expansion. However, there has recently been increasing emphasis on the use of sustainable development principles to meet economic, social, environmental and other goals, described in Chapter 14, which are often conflicting. The sustainomics-based approach leads to a tariff structure that is responsive to these multiple objectives. In the first stage, marginal supply costs are calculated to satisfy the economic (first-best) efficiency objective – using shadow priced future economic resource costs. The structuring of marginal costs permits an efficient and fair allocation of the tariff burden on consumers. In the second stage of developing sustainomics-based tariffs, deviations from strict marginal costs are permitted, to trade off among other important financial, social, political, environmental and economic (second-best) goals. Past studies of the electric power sector in DCs indicate that electricity tariffs have not kept up with cost escalation (Besant-Jones et al., 1990; Munasinghe, Gilling and Mason, 1988). Based on a survey of 60 DCs, electricity tariffs on average declined between 1979 and 1988 from 5.21 cents/kWh to 3.79 cents/kWh in 1986 US constant dollars. The operating ratio (defined as the ratio of operating costs before debt service, depreciation and other financing charges to operating revenue) for the almost 400 power utilities studied, deteriorated from 0.68

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in the 1966 to 1973 period to 0.8 between 1980 and 1985 (Munasinghe, 1991). More recent information confirms these trends. Advances in low-cost metering and switching equipment have made it possible to consider more sophisticated approaches to supply–demand balancing such as spot pricing and load control. In spite of the added costs of implementation, potential savings are large, to both power producers and users. Producers benefit by achieving some of their demand management objectives, such as peak shaving and load shifting. Consumers benefit by being able to select service levels according to their individual needs and by a reduction in total cost. Fernando, Kleindorfer and Munasinghe (1994) have shown that demand management through pricing and interruptible technologies (e.g. load switching) are especially important in DCs, where capital is scarce and shortage costs are higher. Environmental costs of energy reinforce this message even further.

10.2.6 SED options matrix and conclusions Table 10.2 summarizes the impacts of selected options on the three elements of sustainable development. While efficient supply side options (e.g. reductions in T&D losses) have both economic and environmental gains from reduced capital investments and GHG emissions, they do not have obvious social benefits. Efficient end-use options, such as better fuelwood stoves, have benefits relating to all three elements. Although advanced technologies such as clean coal combustion technologies are essential for reducing air pollutants such as CO2 and NOx, which cause respiratory diseases and reduce productivity, many poor countries cannot afford their high costs. Likewise, renewable-energy sources also provide environmental and social benefits by reducing dependence on fossil fuels, but may be more expensive than the latter. Pricing and privatization can have mixed effects, depending on circumstance. SED identifies sustainable energy options, using a comprehensive and integrated framework for analysis, which takes into account multiple actors, multiple criteria, multilevel decision making and constraints. Various methods, including cost–benefit analysis (CBA) and multicriteria analysis (MCA), help to identify ‘win–win’ energy options that satisfy all

Table 10.2 Matrix of selected sustainable energy development options Impact Option

Economic

Environmental

Social

Supply efficiency End-use efficiency Advance technologies Renewables Pricing policy Privatization/decentralization

+ + − − + +

+ + + + + +/−

+ + + +/− +/−


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three elements of sustainable development (i.e. economic, environmental and social). Next, trade-offs can be made among other available sustainable energy options.

10.3 Applying SED to power planning in Sri Lanka In this section, a practical case study of Sri Lanka is presented to show the application of the SED framework. Both CBA and MCA were used by Meier and Munasinghe (1994) to demonstrate how environmental and social externalities could be incorporated into conventional least-cost power system planning in a systematic and efficient manner. In the 1990s, Sri Lanka depended largely on hydropower for electricity generation. However, growing demand has forced planners to build large coal- or oil-fired stations, or hydro plants whose economic returns and environmental impacts are increasingly unfavourable. In addition, there are a wide range of other options (such as wind power, demand side management and system efficiency improvements), that complicate decision making – even in the absence of the environmental concerns. The study is quite unique in focusing on assessing environmental and social concerns at the system-level planning, as opposed to the more usual practice of doing so only at the project level, after strategic sectoral development decisions have already been made (see Chapter 15 for a sustainability analysis of energy projects).

10.3.1 Environmental issues Sri Lanka is one of the more densely populated countries of the world, and land availability is an important issue. In general, hydro plants are in the wet zone areas where there is little vacant land nearby for resettled inhabitants to relocate, while land that is available at greater distances is unattractive to potential evacuees because of the unavailability of water. An effective way of comparing the potential land-related environmental impacts across projects is the area inundated, which varies between zero and 150 hectares kWh. The correlation between the installed capacity and the amount of land to be inundated is poor, because large projects do not necessarily imply worse environmental impacts, and vice versa. The loss of Sri Lanka’s natural forests due to agricultural land clearing, logging and fuelwood use since the 1960s is a major environmental concern. Because Sri Lanka is a small island (65 000 km2), which has been isolated for relatively long periods, there are many endemic species. Among Asian countries, Sri Lanka has the highest level of biological diversity, which is under threat mainly due to loss of natural habitats. Although past power projects have contributed little to forest losses, future projects will be scrutinized carefully for their potential impact on what natural forest areas remain. The air quality throughout Sri Lanka is fairly good, a reflection of the limited extent of industrialization, except in Colombo, and the natural ventilation provided by strong monsoon winds. However, rapid growth in vehicular traffic in Colombo during recent decades has led to a declining trend in air quality (see Chapter 11). It is fairly certain that, at present (2008), the power sector contributes only marginally to air pollution in Sri Lanka. However, this is expected to change significantly once the anticipated coal burning power plants are

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added to the system in around 2011. Acid rain (an increasingly important environmental issue in the Asia-Pacific region) is largely a long-range phenomenon, and its impact in Sri Lanka is as much a function of emission trends in India as in Sri Lanka itself. Global warming and transnational acid rain are conceptually different from local environmental impacts, since, in the former case, the impacts will occur predominantly in other countries (see Chapter 5). Since the main national goal is to maximize welfare in Sri Lanka, decision makers would be unwilling to incur additional costs if the benefits of such actions accrue mainly to other nations. We assume that Sri Lanka will be reimbursed by the global community for incremental costs of GHG mitigation efforts. As the generation mix shifts from hydro to fossil fuels, thermal power plant sites will be needed on the coast, with potential environmental risks to major economic activities such as foreign tourism and marine fisheries (which employ about 100 000 people, and is the largest source of animal protein for Sri Lanka). The main environmental issue is the discharge of heated effluents into coastal habitats that contain many temperature-sensitive ecosystems, including (1) coral reefs, sea grass beds, benthic communities and mangroves; (2) free floating zooplankton and phytoplankton communities; and (3) nursery grounds for fish and prawns. 10.3.2 Methodology Power-sector strategies that have beneficial impacts on economic, social and environmental goals are the first priority, e.g. energy-efficiency measures that reduce costs and polluting emissions. However, most options involve trade-offs requiring MCA (see Section 3.5) – e.g. wind plants that provide substantial environmental benefits but are costly. The overall methodology (Figure 10.5) involves: (1) defining the potential options; (2) selecting and defining attributes selected to reflect planning objectives; (3) economically valuing impacts (where possible) and including them in overall system costs; (4) quantifying remaining attributes (using non-economic measures) where economic valuation is difficult; (5) translating attribute value levels into value functions (known as ‘scaling’); (6) displaying results in the trade-off space, to facilitate decision making; and (7) identifying key options for further study, by eliminating inferior ones. Here, we do not assign weights to attributes and aggregate the results to end up with a single overall ranking of options. 10.3.3 Application to the Sri Lanka power sector Policy option definition A variety of options were examined, including siting, pollution control mitigation and technology options, without making a priori judgements about their feasibility. The main policy options examined, beyond variations in the mix of hydro and thermal plants, included: (1) demand side management – e.g. compact fluorescent lighting; (2) renewable-energy options (using the illustrative technology of wind generation); (3) improvements in system efficiency (using more ambitious targets for transmission and distribution losses than the base

10 Energy-sector applications environmental and social issues

quantify

environmental and social attributes

MCA

no

economic valuation

335 define siting, technology and mitigation scenarios

no

yes

economic attribute (system NPV)

trade-off curves

define additional scenarios

apply valuation techniques

economic analysis

policy analysis

Figure 10.5. Methodology for the Sri Lanka power sector study. Source: Meier and Munasinghe (1994).

case assumption of 12% by 1997); (4) clean coal technology – e.g. pressurized fluidized bed combustion (PFBC) in a combined cycle mode; and (5) pollution control technology options – e.g. fuel switching and pollution control options like using imported low sulphur oil for diesels and fitting coal-power plants with flue gas desulphurization systems. Attribute selection The attributes selected reflected issues of national significance. They were limited in number, because the more attributes considered, the more complex the analysis, and the higher the probability that the results will be harder for decision makers to interpret. Key environmental attributes were expressed as present discounted values. Carbon dioxide emissions were the proxy for potential impacts of climate change, assuming linearity of impacts – since Sri Lanka is a very small GHG contributor. Population-weighted increment in fine particulates and nitrogen oxides attributable to each source were used to capture health impacts. A simple Gaussian plume model was applied to all major sites, and incremental ambient concentrations for 1 km2 cells were estimated inside a 20 km radius, and then multiplied by the population in each cell. Sulphur dioxide and nitrogen oxide emissions represented air pollution impacts like acid rain. A probabilistic index was derived for biodiversity impacts. Employment creation was used as a typical social impact. It is a key goal of national policy, especially for youth. What is captured in this attribute is the separate, and purely political, objective of employment creation, and is to be distinguished from strictly economic benefits that would be captured by the use of shadow wage rates (that reflect high unemployment) in the construction cost estimates.

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Attribute quantification The biodiversity attribute illustrates the problems of quantification. Detailed site-specific information at power plant sites is unlikely to be available to planners. Thus, an index must be derived that gives decision makers information about the likelihood that the detailed environmental impact assessment will reveal the presence of an endemic species, harm high biodiversity ecosystems, or affect already vulnerable habitats. There are many practical problems in deriving such a probabilistic index. First, the value of the area lost is a function of the remaining habitat. For example, the loss of the last hectare of an ecosystem would be unacceptable, whereas the loss of one out of 1000 hectares would be tolerable. Second, ecosystems may require a minimum area for long-term survival, which implies that the value function would need to tend to infinity as it approaches that minimum value. Some impacts resist direct quantification, even in terms of a probabilistic scale. For example, the quantification of potential damages to aquatic ecosystems from thermal discharges is difficult. Discharges into the well mixed surface layer would generally repel fish. On the other hand, discharges below the thermocline are beneficial, as the up-welling effect caused by plume buoyancy brings nutrients to surface. However, it is very difficult to assign numerical values to this general function. Instead, a rough calculation may be used to compare different sites by defining an acceptable environmental risk – e.g. a temperature increase less than 1 °C at the surface. The surface area over which this criterion is exceeded may be calculated for each cooling system design proposed.

10.3.4 Illustrative results and conclusions After defining both options and attributes, the multidimensional trade-off space was derived. Using the ENVIROPLAN model, values for each environmental attribute and the system costs (i.e. average incremental cost over a 20-year planning horizon) were calculated for every option, with results displayed as a series of two-dimensional trade-off curves. Finally, the candidate plans for further study were derived by examining dominance relationships among all criteria simultaneously. Figure 10.6 shows typical trade-off curves for biodiversity and health impacts. The ‘best’ solutions lie closest to the origin. The trade-off curve or set of ‘non-inferior’ solutions represents options that are superior, regardless of the weights assigned to the different objectives. For example, in Figure 10.6(b), the option ‘iresid’ (use of low sulphur imported fuel oil at diesel plants) is better on both the cost and the environmental objective than the use of flue gas desulphurization systems (option ‘FGD’). Figure 10.6(a) shows a different trade-off curve between the biodiversity index and average incremental cost. Most of the options have an index value that falls in the range 50–100. The ‘no hydro’ option has a near-zero value, because the thermal projects that replace hydro plants in this option tend to lie at sites of poor biodiversity value (either close to load centres or on the coast). Wind plants would require rather large land area, but the vegetation of this land on the south coast has relatively low biodiversity value. Thus, the best

5.9 +Kukule HD

5.8 5.7 no DSM supply costs (cents/kWh of demand)

5.6 5.5 5.4

+FGD

?

5.3

low coal

5.2

iresid T&D>11

5.1 +wind 5.0 no hydro

trade-off

4.9 +ku 4.8 +UO2001 4.7

0

100

200

300 400 biodiversity loss index

500

600

(a) 5.9 +Kukule HD

5.8 5.7 supply costs (cents/kWh of demand)

no DSM 5.6 5.5

low coal + iresid

no coal

+FGD

5.4

low coal

5.3 iresid

5.2

Mawella >D T&D>11

5.1 +wind 5.0

trade-off

4.9 4.8

+UK2001

quadrant III +PFBC

no hydro base case (with DSM) +UO2001

4.7

2

3

4 5 NPV of health impacts (2010; r = 10%)

6

7

(b)

Figure 10.6. Trade-off between (a) economic cost and biodiversity impact and (b) economic cost and health impact. Source: Meier and Munasinghe (1994).

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options (or non-inferior) curve includes the no hydro option, and run-of-river hydro options that require essentially zero inundation. Note that the extreme outlier at the top right hand corner is the Kukule hydro dam, which has a biodiversity loss index (B = 530) that is much larger than for other options (B = 50–70). The case study yielded four useful conclusions, showing how MCA can assist decision makers, and five practical policy recommendations to help incorporate environmental issues into the system planning process. First, impacts for which valuation techniques are quite straightforward and well established (like valuing opportunity costs of lost production from inundated land, or benefits of establishing fisheries in a reservoir), tend to be quite small in comparison to overall system costs. Their inclusion in the benefit–cost analysis does not materially change results. Second, even where explicit valuation may be difficult (like health effects of air pollution), implicit valuation using trade-off curve analysis provides useful guidance to decision makers. For example, the study showed that the value of human life which justified flue gas desulphurization at coal power plants was about US $1.5 million. This is much greater than the cost of radically modernizing regional hospitals. Third, certain options were clearly inferior (or superior) to all other options when one examines all impacts together. For example, the high dam version of the Kukule hydro project could be excluded from further consideration due to poor performance on all attribute scales (including economic cost). On the other hand, implementation of certain demand side management measures dominates all other options, because they yield gains in terms of both economic and environmental criteria. Fourth, it is possible to derive attribute scales that can be useful proxies for impacts that may be difficult to value. For example, use of the population-weighted incremental ambient air pollution scale as a proxy for health impacts leads to some key conclusions that are independent of the specific economic value assigned to health effects. If the health effects of pollutants from fossil-fuel combustion (particularly fine particulates and nitrogen oxides) are to be reduced, then the most effective strategy for lowering the overall population dose is to install tighter pollution controls at oil-burning power plants located in or near urban areas, rather than installing FGD systems at the more remote coal-power sites. Finally, specific recommendations on priority options for practical planning, include the need to: (1) examine systematically demand side management options, especially fluorescent lighting; (2) examine whether the present transmission and distribution loss reduction target of 12% ought to be further reduced; (3) examine the possibilities of PFBC technology for coal power; (4) replace some coal-fired power plants (on the south coast) by diesel units; and (5) re-examine cooling system options for coal plants.

10.4 Energy policy options This section summarizes selected policy implications of the case study in Section 10.3 and subsequent studies of energy use in the Sri Lanka power sector (Munasinghe and Meier,


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2003a, b). In particular, we seek to make power-sector development more sustainable by expanding on the recent debate on restructuring and reform of the sector to achieve the basic goal of an adequate and affordable electricity supply to consumers. Sri Lanka will continue to pay the costs of the failures of decision making since the beginning of the twenty-first century. Most of the generating capacity added over the past decade has been based on auto-diesel, which is not only expensive, but also the most volatile in cost. Moreover, the environmental opposition to coal generation has been unjustified, e.g. the actual environmental impacts of diesel generation in densely populated urban areas is greater than those of modern coal-based plant. In 2005, about half of all generation was oil-based. While the private sector has captured a larger share of generation, the increased cost to users resulting from diesel far outweighs the benefits of private-sector competition in generation. The new National Energy Policy recognizes that Sri Lanka is too dependent on oil-based generation. To diversify supply and lower cost, it is imperative to seek a more balanced generation mix by moving to coal. Over-reliance on diesel generation raises costs, undermines trade competitiveness and imposes environmental costs. The first step in the right direction was taken in 2006, when construction began on a 300 MW coal plant at Norochalai (with subsequent planned expansion to 900 MW).

10.4.1 Environmental impacts GHG mitigation The first priority for GHG emission reduction in Sri Lanka is power-sector reform (which would reduce T&D losses) and the implementation of a comprehensive DSM lighting programme. Unlike in India, reform in Sri Lanka is win–win with respect to both net economic benefits and GHG emission reduction. Once reform has been implemented, use of residual oil for diesel-power generation is the next GHG mitigation option that would be the easiest to implement from an institutional and managerial standpoint. It will likely bring net economic benefits as well. However, the feasibility of this option depends on an expansion of Sri Lanka’s domestic refinery capacity, which is still under study. One promising least-cost option includes additional DSM and T&D loss reduction (beyond levels envisaged in the first stage of reform), plus an aggressive implementation of 45 MW of mini-hydro schemes. While these are ‘win–win’ (economic gains and reduced GHG emission), there are major financial and institutional barriers. Therefore, mini-hydro should continue to be supported by GEF and ESD (see Section 10.4.4). Dendro-thermal power plants could reduce GHG emissions at a reasonable cost, subject to field verification of key issues about plantation management, land and labour availability and plant-gate cost. Therefore, a pilot project is recommended of at least a 1 MW power plant, with a fuelwood plantation of around 400 ha. Another option would be to study the costs of expanding the Norochalai coal power plant with a second 300 MW plant co-fired with fuelwood – a proven technology. If co-firing were too costly, the wood from the pilot plantation could still be sold in the Colombo fuelwood market, thus reducing project risks.

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Sri Lanka has substantial wind power potential, but the costs are high. The maximum wind scenario examined here has a cost of avoided carbon of US $65/tonne. Even if capital costs were to fall to US $700–800/kW (currently over US $1000/kW), this would still be an expensive mitigation option – given the low plant factors achievable. The poor wind speeds and capacity factors achieved at the 3 MW pilot project on the south coast suggest the need for a more comprehensive wind resource assessment before committing to large-scale wind development. The solar homes system (SHS) is justified by the importance that is attached to rural lighting (and the expense and difficulties of extending grid service to remote villages). However, SHS has a low priority as a GHG mitigation measure. Even under optimistic assumptions about market penetration, the GHG emissions reduced by the SHS programme are less than 1% of the value achieved through reforms. Local environmental impacts The review of local environmental impacts is deferred to the end of Chapter 11, after analysing sustainable transport options for Sri Lanka.

10.4.2 Hedging strategies High sulphur fuel oil can be imported at relatively low cost from Middle Eastern refineries, and in the past this was often a cheaper fuel than coal. However, given the present rising trend in oil prices (see Section 10.1.1), and the impact of the 1970s oil shocks, the Government of Sri Lanka may be cautious about major commitments to large steam-cycle oil plant. While the historical dependence on hydro insulated the electric sector from the 1970s oil price shocks, the risks of overdependence on hydro were amply demonstrated during the 1996 and 2001 droughts, which caused reduced GDP growth by over 1%. Thermal generation reduces this hydro risk, but replaces it with a new dependence on oil. One useful hedging strategy is dual-firing capability at the coal plant – with oil or wood co-firing. A key issue here is the amount of oil storage to be provided. The larger the volume of storage, the larger the capital costs, but the greater the ability to buy and store oil during periods of low oil prices and to avoid futures-market hedging.

10.4.3 Petroleum-sector issues In 2003, Sri Lanka consumed about 3.4 million tonnes of oil products (Table 10.3). About half (mainly diesel) was imported, and the rest was produced at the Ceylon Petroleum Corporation’s (CPC) refinery at Sapugaskanda (which imported 2 million tonnes of crude in 2003). The recent introduction of competition in the petroleum sector, by selling one-third of CPC’s monopoly share of the oil market to the Lanka Indian Oil Company (LIOC), was beneficial. However, as in the case of the power sector, the presumption that all can now be


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Table 10.3 Sri Lanka Petroleum product consumption, kilotonnes

Petrol (90 octane) Petrol (95 octane) Auto-diesel Super-diesel Kerosene Furnace oil Avtur Naphtha LPG Total

2001

2002

2003

244 5 1675 49 228 811 138 14 141 3305

277 9 1752 47 229 780 114a 56 157 3423

328 13 1652 42 212 715 139 102b 161 3360

a

Decline reflects the drop in tourist arrivals following the terrorist attacks at Colombo International Airport in 2001. b Increase reflects commissioning of the CEB naphtha-fired CCCT in December 2002. Source: Central Bank (1998, 2003).

left to the interplay of market forces carries long-term risks. The history of world oil markets since the 1960s illustrates the need to balance short-term market considerations with supply security, especially for transport (see Chapter 11). The supply–demand balance for, and the relative prices of, various transport fuels depend on the availability of refined outputs. Thus, the future of the Sapugaskanda refinery in a privatized sector raises key issues. There is no requirement in the present agreement between the Government and LIOC that the latter should purchase some or all of its supply from the local refinery. If the restructuring of the sector evolves to include more players, the market share of Ceypetco (CPC) may drop below 30%, with the result that, unless the other players purchase a significant share of their requirement from Sapugaskanda, the refinery throughput will fall to levels at which it is no longer profitable. Sri Lanka will not wish to run an unprofitable refinery, and it is economically inefficient for the refinery to be protected by customs duties (which will simply raise the price to all consumers). However, if the refinery closes, then Sri Lanka will become entirely dependent on the international players dominating Asian markets. This was the situation faced by Sri Lanka in the 1950s, which led to nationalization of oil at that time. Several options to address this problem may be considered. For example, if the Sapugaskanda refinery can match the landed cost of products as calculated by the new pricing formula (based on Platts), then the private-sector players could be required to purchase locally, in the broader national interest. In short, such issues need to be considered in a national sustainable energy planning process that balances the various long- and short-term interests, including the security of supply. All stakeholders, including private companies, should be consulted, but the final decision will remain the responsibility of the Government.

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10.4.4 Renewable energy for off-grid electrification As described in greater detail in Chapter 15, the Energy Services Delivery (ESD) project is one of the most successful renewable-energy programmes in the World Bank/GEF portfolio. ESD included the SHS and village hydro components, and a grid-based mini-hydro programme, which established a viable and sustainable private-sector business activity developing small hydro-projects. Consumer surplus should be included in the economic benefits for off-grid electrification systems. This is supported by the empirical evidence – even poor households are willing to pay much more for higher quality electric lighting and TV viewing than alternative kerosene/ battery cost. While grid-based electrification is the long-term goal, access targets are often unrealistic, because grids are extended more for political objectives than for sound economic reasons. The result is high losses, poor grid service and unsustainable financial losses for the utility. In Asia, new models for rural electrification have the common theme of transparent subsidies and clear separation of O&M operations – the latter requires effective local institutional capacity.

10.4.5 Key power-sector priorites Energy planning, particularly by the public sector, is often unfairly maligned, in the context of market liberalization and private-sector involvement. Yet Sri Lanka’s experience suggests that energy planning can be effective for guiding change and mobilizing capital, provided it is coupled with the necessary political will. The institutions established in the early 1980s (when President Jayewardene was also the Minister of Energy) were highly effective. One of the world’s first integrated national energy plans was practically implemented. The Lanka Elecricity Company (LECO) was established with autonomous management, but under public ownership. LECO is a model for South Asia – e.g. reducing T&D losses from over 50% to less than 8% was a remarkable achievement under difficult circumstances, including years of civil strife, a poor tariff environment and disputes with CEB over large industrial customers. The keys to LECO’s success were the commercialization of operations and the political will to enforce that mandate. In practice, this meant direct support from the President when political pressure was put on LECO to relax enforcement of those measures introduced to reduce commercial losses. Planning by the main-sector institutions begun in the mid 1980s suffered due to lack of implementation. It is quite clear that the failure to ensure adequate capacity since the mid 1990s, and dependence of the CEB system on costly power generation (based on autodiesel), was not a failure of planning, but a problem of political will to implement plans. Sri Lanka has not been well served by advice from those with a vested interest in privatization and private-sector generating plants. As in India, the view that the introduction of independent power producers would lead the way to reform was unsound (and, in the case of India, this was promoted in the early 1990s mainly by corrupt persons). While the scale of


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failures in Sri Lanka is much smaller than at Dabhol, the result is much the same – risk of power shortages, power generation plants using expensive fuel (auto-diesel) and located in environmentally harmful areas (like the barge-mounted plant in Colombo harbour) and vested interests (including donors promoting privatization) proposing unrealistic and unviable projects. The problems of the power sector cannot be solved by restructuring alone, and competition in the marketplace will not necessarily ensure timely investments of new capacity. Examples include the California power crisis (see Section 10.2.4) and the inadequacy of the power transmission infrastructure in Europe, which caused widespread and costly blackouts in Italy in September, 2003. Because of long time lags, the relevant regulatory body must ensure a coherent investment planning process in the public interest, as recognized in the new Sri Lanka National Energy Strategy. A regularly updated long-term generation expansion plan for the electricity sector, and a parallel renewable-energy plan, is included. The Indian experience with the newly established electricity regulatory commissions shows that, despite their nominal independence and the unbundling of sector operations, political interference remains a problem. While sector reform and a predictable and stable tariff regime are necessary conditions for successful mobilization of private capital for major energy infrastructure projects, an important priority for energy-sector development is a sustainable settlement of the ethnic conflict.

10.5 Assessing the sustainability of energy policies in South Africa This section illustrates the SED approach by summarizing a policy-relevant, sustainable development assessment of energy policy option in South Africa, carried out by Winkler (2006), using MCA.

10.5.1 Status of energy and electricity in South Africa Making energy production and use more sustainable is a central challenge in South Africa’s future development path. Growth rates for electricity consumption and economic output have been correlated. The electricity supply industry was originally driven by mining needs. The availability of cheap coal and electricity helped to establish manufacturing industries. The apartheid government made large investments to develop a synthetic oil industry and local nuclear capacity. The democratic government has shifted the focus from supply to demand – to improve household access to electricity and make energy services more affordable. Coal currently accounts for 75% of the primary energy supply (DME, 2003) and for over 90% of the total licensed capacity of over 43 000 MW (NER, 2002). By 1948, the electricity industry was consolidated into a large and powerful, state-owned, vertically integrated monopoly (Eskom). Large power projects were initiated to meet demand up to 16% annually during 1972–1982 (Eberhard, 2003). Later, growth slowed, leaving a large excess capacity in the 1980s and 1990s, which helped to keep prices low. Power supply in South Africa was limited to established towns and areas of economic

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activity. In 1993, only 36% of the total population had access to grid electricity. The first phase of the National Electrification Programme (1994–1999) increased electrification to about 66% nationally – 46% in rural areas and 80% in urban areas (NER, 1999). Yet, onethird of the population still has no electricity, especially in rural areas. Major changes are taking place at present in both the electricity industry (due to restructuring) and the petroleum sector (with the establishment of a Gas Regulator). The option of introducing LNG into South Africa is being examined (CEF, 2005). The amended Petroleum Products Act will alter licensing rules for petrol stations to give government more control, while the Petroleum Pipelines Bill is expected to establish pricing and access rules for oil and gas pipelines. Energy-related environmental impacts are of increasing concern. Monitoring of emissions will soon be required through the National Air Quality Management Bill. Diversity of supply has been emphasized as South Africa intends to use every energy source optimally – coal, gas, oil, nuclear and renewable energy. The initial focus has been on importing natural gas from Mozambique and possibly Namibia, which could promote a major shift away from coal (DME, 2001; Marrs, 2000a, b). Renewable-energy sources are another option for increasing diversity, while focusing on sharing hydroelectricity from within the South African Power Pool (SAPP). Eskom has identified 9000 MW of potential regional imports (excluding Grand Inga in the Congo). The government target is that new renewable energy will contribute 10 000 GWh to energy supply by 2013 (approximately 4% of demand). Good progress has been made in extending access to electricity, although affordability and productive use remain difficult issues. The main energy goals of the government include greater access to affordable energy services, improved energy governance, stimulating economic development, managing energy-related environmental impacts and securing supply through diversity (see Section 10.2 on SED goals).

10.5.2 Analysis and results The SED indicators shown in Table 10.4 were selected to reflect South Africa’s development objectives, to be consistent with energy policy goals and to mark progress toward sustainability. Table 10.5 summarizes the policy options that were assessed for their sustainability, and Table 10.6 shows the results for residential energy use. Figure 10.7 ranks the different policies according to three sustainable development indicators – more affordable electricity (social); lower total power system costs (economic); and lower emissions (environmental). The higher the number, the more sustainable the policy. No clear winner emerges. If the priority were to reduce energy system costs, the importing of gas or hydroelectricity would be favoured, since the economic indicator is at the outer edge of the triangle, representing a more sustainable policy. Both imports reduce capital and overall system costs. The environmental priority of reducing emissions in South Africa would favour two domestic options, even though they show higher costs, i.e. renewables and the more costly nuclear pebble bed modular reactor (PBMR).


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Table 10.4 Indicators for sustainable energy development Indicator

Units

Economic Total cost of energy system Marginal cost of electricity supply Diversity of electricity fuel mix – domestic sources, billion Rands

billion Rands cents/kWh %

Environmental Local air pollutants in 2025 sulphur dioxide nitrogen oxides carbon monoxide Global greenhouse gases Social Fuel consumption in residential sector Cost of energy services to households shadow price of residential electricity shadow price of non-electric fuels Monthly expenditure on electricity

kilotonnes SO2 tonnes NOx tonnes CO megatonnes CO2-equiv. petajoules cents/kWh Rands/gigajoule Rands per household per month

Table 10.5 Policy cases in residential energy and electricity supply sectors Short name Households SWH

CFL Eff house

LPG switch Combined elec

Key features cleaner, more efficient water heating is provided through increased use of solar water heaters and geyser blankets; the costs of SWH decline over time, as new technology diffuses more widely in the South African market more efficient lighting, using compact fluorescent lights (CFLs) spreads more widely, with a slight further reduction in costs beyond that achieved already the shell of the house is improved by insulation, prioritizing ceilings; since the technology has zero fuel costs, bounds are placed to ensure that no further building takes place households switch from electric and other cooking devices to LPG stoves and rings the combined effect of all the above policies

Electricity Renewable energy share of renewable power rises to meet the target of 10 000 GWh by 2013; shares of solar thermal, wind, bagasse and small hydro rise over the base case; new technology costs fall as global production increases PBMR production of PBMR modules for domestic use increases capacity of nuclear up to 4480 MW by 2020; costs decline with national production and initial investments are written off

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Table 10.5 (cont.) Short name

Key features

Hydro

share of hydroelectricity imported from SADC region increases up to 15 GWh by 2010, from 9.2 GWh in 2001; as more hydro capacity is built in Southern Africa, the share increases sufficient gas is imported to provide 1950 MW of combined cycle gas turbines, in units of 387 MW fluidized bed combustion using discarded coal, a low-cost resource, is part of the base case already; the implications of what would have happened without this resource are explored

Gas Base w/out FBC

The combined case scores poorly on costs, making emission reductions expensive. Diversity of supply is shown in Figure 10.7 only by the increased share of renewables. The renewables option still achieves a better mix among other fuels, but another indicator (e.g. reduction in coal use) would be needed to show that PBMR achieves the greatest diversity of supply in moving away from coal dependency. Both domestic options reduce local air pollutants and GHGs by similar percentages. Figure 10.8 shows a more complex set of sustainable development indicator rankings for the same power supply policy options. Again no SED option is clearly superior, since the ranking of policies changes sharply depending on the indicator. Figure 10.9 shows results for residential policies. Here a clearer picture emerges. Within the context of meeting the basic energy development objective, two residential policies show the greatest capability for making development more sustainable. The triangles for efficient houses and SWH/GB completely contain those for CFLs and LPG cooking. Efficient houses and SWH/GB make the greatest fuel savings and thus save the greatest energy costs for households. The policies reduce the electricity burden for households, particularly for poorer urban electrified ones. Increased affordability makes social disruption less likely. These two options also contribute the most to cleaner fuel use and improve environmental quality. Combining all policies seems to be a very sustainable option – as indicated by the largest triangle. Comparing both residential and electricity policies against each dimension of sustainable development provides us with some idea of the synergies and trade-offs. There are clear win–win cases for residential policies. However, no single electricity supply option is preferable economically, socially and environmentally. One implication is that more tradeoffs are required. Another is that short-term economic costs should not be the only factor in identifying durable long-term solutions. The results identify home energy policies that have greater potential for making development more sustainable, including efficient houses and clean, efficient water heating. Renewable energy had multiple benefits among electricity supply options, but the tradeoffs with the lower costs of imports require further consideration. Combining residential and

RHE RLE

Cost of energy services to households Cost of electricity in common units Cost of energy services to households: shadow price of non-electric fuels, residential Coal for households Biomass LPG Paraffin Candle wax Monthly electricity cost

Total fuel use

Renewable energy

Liquid fuels

Social Fuel consumption in residential sector (petajoules) Electricity

Indicator

87 16

3.5 30 149.4 96.9 70.3

Rand/gigajoule

Rands per household per month

98.9 116.8 51.9 58.9 1.7 3.5 201.1 213.5 37.8 105.1

Base case

2014 2025 2014 2025 2014 2025 2014 2025 cents/kWh Rand/gigajoule

Year or unit

Table 10.6 Overview of results for residential energy use

78 15

3.5 30 149.4 96.9 70.3

93.1 104.9 43 39.3 7.9 16.7 195.3 202.3 34.2 95.1

Efficient houses

80 15

3.5 30 149.4 96.9 70.3

98.9 116.8 51.9 58.9 1.7 3.5 201.1 213.5 34.8 96.7

CFLs

80 15

3.5 30 149.4 96.9 70.3

95.9 110.3 51.9 58.9 1.7 3.5 201.5 214.4 34.8 96.7

80 15

3.5 30 149.4 96.9 70.3

96.4 112.6 41.3 36.1 9.5 20.1 195.2 202.1 34.8 96.7

Water heating – LPG for SWH/GB cooking

78 15

3.5 30 149.4 96.9 70.3

98.3 115.5 51.9 58.9 1.7 3.5 200.5 212.3 34.2 95.1

Residential policies combined

164 62

Base case

kilotonnes CO2 tonnes CH4 tonnes N2O 6120 29.78

630 053 50 325 8171

kilotonnes SO2 3571 tonnes 888 450 NMVOC tonnes NOx 2 156 438 tonnes CO 4 923 479

Year or unit

Economic Total cumulative cost of energy system billion Rands Annualized investment in all residential billion Rands technologies in 2025

Environmental Local air pollutants (in 2025) Sulphur dioxide Non-methane volatile organic compounds Nitrogen oxides Carbon monoxide Global GHGs (in 2025) Carbon dioxide, total Methane Nitrous oxide

UHE ULE

Indicator

Table 10.6 (cont.)

6119 30.23

622 540 50 234 8065 6119 29.58

629 686 50 323 8165

2 155 275 4 923 416

2 132 925 4 921 832

151 57

3568 888 432

CFLs

3524 888 038

148 56

Efficient houses

6115 29.71

624 117 50 261 8082

2 137 627 4 922 246

3531 888 139

151 57

6121 30.65

628 685 50 380 8149

2 151 339 4 923 237

3559 888 387

151 57

Water heating – LPG for SWH/GB cooking

6115 29.75

621 827 50 301 8052

2 129 828 4 921 730

3517 888 011

148 56

Residential policies combined


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economic: reduced energy system costs 5 4 3 2

1 = more sustainable 5 = less sustainable

1 0

social: reduced cost of electricity overall

environmental: reduced emissions (local and global)

renewables

PBMR

import hydro

import gas

combined electricity

Figure 10.7. Electricity supply options ranked by three economic, social and environmental indicators.

economic: reduced system cost 5


4 3

diversity: reduced coal

environmental: reduced local pollutants

2 1 0

diversity: increased renewables

environmental: reduced GHGs

social: reduced cost of electricity supply import gas

import hydro

PBMR

renewables

combined electricity

Figure 10.8. Electricity supply options ranked by six economic, social and environmental indicators.

350

Sub-national and system applications environmental: reduced emissions 5

4 3


2 1

0

social: reduced home fuel costs

economic: reduced energy system costs

CFLs

efficient houses

SWH/GB

combined residential

LPG for cooking

Figure 10.9. Residential energy options ranked by three economic, social and environmental indicators.

electricity policies would provide a mix that overall provides a durable balance of economic development, social sustainability and both local and global environmental benefits. The approach has been demonstrated for South Africa, but will resonate with other rapidly industrializing developing countries. Finally, the study confirms that national sustainable development is the appropriate starting point (conceptually and methodologically) to determine the energy and mitigation policies.

10.6 Making electricity development more sustainable in the UK 10.6.1 Background of the UK electricity system Currently the UK’s electricity supply is still highly centralized. Decentralized energy (DE) represents only 7.3% of total capacity and 7.2% of generation. Large-scale co-generation (>1 MWe) has the largest share of DE capacity (3.1 GWe), but other DE sources, such as onsite renewables, are growing rapidly (DUKES, 2006). In terms of fuel use, most generation in the UK is coal-fired (31.3%), with natural gas a close second (29.1%). However, gas is


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increasingly important, and declining North Sea gas reserves have raised concerns about energy security. Nuclear is another important energy source (18.2%). Other sources of energy for power come from oil (1.14%), hydro (0.42%), other renewables (2.99%) and other fuels (1.55%). The WADE Economic Model The WADE Economic Model calculates the economic and environmental impacts of supplying incremental electrical load growth with varying mixes of DE and central generation (CG). It uses detailed and comprehensive data about existing electricity generation facilities, as well as future fuel price trends and technology development. Starting with known generating capacity for year 0 and projections for capacity retirement and load growth, the model adds user-specified capacity to meet future growth and retirement over a 20-year period. It helps to make policy decisions by comparing concrete alternatives, using a sensitivity analysis of important variables such as fuel prices and demand growth, and allowing direct comparison between different power-system-expansion plans. In this study, the model was used to analyse five cases for new capacity to meet incremental demand over 20 years, with the mix of future plant to be added ranging between two extremes, i.e. [0% DE, 100% CG] and [100% DE, 0% CG]. For each of the five scenarios, the results give the total capital costs (i.e. generation, transmission and distribution, T&D) over the 20year period, as well as the retail costs (future costs adjusted or levelled to their present value), the annual CO2 and other pollutant emissions from new and total generation and the fuel use (both absolute and by share of generation) in year 20. The model also gives results for intermediate years within the 20-year analysis period. These results relate directly to national policy goals, and are essential for sustainable development decision making.

10.6.2 UK energy scenarios Two main illustrative scenarios are shown in Figure 10.10. Baseline – central nuclear (100% CG) The baseline scenario called ‘central nuclear’ assumes a 5% demand growth per year with 100% CG, and represents a likely future electricity system, based on the expected responses of the market and government to the existing issues. It assumes that new nuclear capacity will be built in the second decade of the analysis to replace existing plants, and assumes that nuclear will comprise 20% of the generation capacity at 2002. Until new nuclear plants become operational, it mainly uses gas combined-cycle gas turbines (CCGT) to meet demand, but also some coal-fired generation to limit the UK’s reliance on gas imports. Renewable generation, mostly wind energy, is increased gradually. Main alternative (100% DE/renewables) DE/renewables is the main alternative. It had all the same inputs and assumptions as the central nuclear case, but a different generation mix: 75% of all new capacity was decentralized, while

352

Sub-national and system applications 100% 24 80%

42

new capacity

7 60%

renewable bio-energy

13

oil 12

nuclear gas

40% 43

coal 39

20% 13

7

0% central nuclear

DE/renewables scenarios

Figure 10.10. Baseline and main alternative scenarios.

25% consisted of renewables (centralized). No new nuclear capacity is built, while existing plants are retired at projected rates. There are no new centralized fossil-fired plants either, so that all new CG (25% of the total market) is renewable (mostly wind and bioenergy). The 75% market share of DE is mostly gas-fired combined heat and power (CHP), but shares of microCHP and on-site renewables will increase over the 20-year period.

10.6.3 Main results and conclusions We analyse the model results within the sustainomics framework of making energy development more sustainable in the UK, using three typical indicators: (1) economic – delivered energy costs; (2) environmental – CO2 emissions; (3) socio-political – fuel used (representing dependence on foreign energy imports and reduced energy security).

Table 10.7 shows that the main alternative (with a more decentralized electricity supply system) results in lower delivered electricity cost (and lower capital costs), lower carbon emissions and less fuel use. Thus, it is clear that the decentralized scenario is the more sustainable option, as it is superior in all three dimensions of sustainable development – i.e. the triangle for 100% DE/renewables in Figure 10.11 is contained within the triangle of 100% CG, showing that the former is cheaper, less polluting and more energy secure. The main reason for the cost savings is that the model assumes that DE requires less T&D capacity than CG, because it generates electricity much closer to the point of use. This assumption is valid, as most T&D capacity will require replacing within the next 10–20 years. The UK electricity demand is expected to grow in the commercial and residential


353

Table 10.7 Main results Scenarios

Capital costs, generation and T&D Delivered costs (£/kWh) CO2 emissions (megatonnes/year) Fuel use (petajoules/year)

100% CG

100% DE/renewables

Saving

Percentage saving

£70 billion

£51 billion

£19 billion

27

0.0683 36.75

0.0582 33.92

0.0101 2.83

15 7.7

2303

2163

140

6.1

delivered costs (£ /kWhr)

100% CG 100% DE/ren

fuel use (PJ/year)

CO2 emissions (Mt/year)

Figure10.11. Sustainability comparison of 100% CG and DE/renewables scenarios.

sectors, thus requiring additional T&D as well as generation capacity, with CG requirements being larger than DE. In addition, new CCGT power stations would most probably be built where new gas pipelines from the European continent come in, thus requiring new transmission lines to connect them to the grid. Part of the savings made by the DE cases is also due to the higher operating efficiency of these technologies, particularly through co-generation and reduced transmission losses. Fuel use and CO2 emissions are most strongly affected by this aspect. Note that the CG mix of the baseline scenario only introduces new nuclear generation from 2014, reflecting its long lead time. Consequently, the 100% CG scenario also includes a substantial amount of new gasfired CCGT. This explains the savings in CO2 emission and fuel use of the DE/renewables case, and shows that building any new gas-fired power stations that do not recover heat is clearly problematic in terms of Kyoto commitments and energy security. Some sensitivity studies, assuming changes in some key assumptions, did not change the main conclusion of the study that DE options were more sustainable than CG options.

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Fuel-price sensitivities Sensitivity analysis of fuel prices, for which future trends are clearly uncertain, indicates that the effect of changes in fuel-price trends on the retail price is significant, and it affects DE/ renewables more than CG, because retail prices are higher than wholesale prices. However, the results show that the benefits of DE/renewables are maintained at fuel-price rises of up to 10% per year. Generation portfolios When impacts of not building new nuclear or gas CCGT power stations were considered, carbon emission and fossil-fuel use increased, while costs remained largely unchanged. High reliance on gas imports from continental Europe confirmed that these were not attractive alternatives. Demand growth Reducing demand growth from 0.5% per year to 0% results in carbon emission savings comparable to a nuclear replacement programme (central nuclear scenario), and also reduces capital costs and fuel use by almost 20% and 10%, respectively. With zero demand growth, retail prices were slightly higher in the centralized case, because many costs are fixed, so that, with lower total generation, the unit price is higher. However, DE/renewables retail prices decreased with lower demand growth. Another more radical scenario (by Greenpeace) was also modelled, with a demand reduction of 0.5% per year through energy conservation, assuming rapid development of renewables and energy-efficiency measures surpassing government targets. The results were slightly better than for the 100% DE/ renewables scenario.

11 Transport-sector applications1

This chapter continues our coverage of sustainomics applications to economic infrastructure sectors, focusing on transport (including fuel-pricing policy). Section 11.1 reviews generic priorities for sustainable transport, and discusses key issues worldwide, as well as economic, social and environmental linkages. Then we examine how transport policy could be made more sustainable in a typical developing country. In Section 11.2, health damage externalities due to transport-related air pollution in Sri Lanka are discussed, including a literature review, an estimation of damage costs from local air emissions using the benefit transfer method and finally an assessment of the specific health benefits of introducing unleaded petrol. Section 11.3 covers another classic externality – the effects of traffic congestion in the city of Colombo, including estimation of the cost of time wasted. Section 11.4 analyses several specific infrastructure projects and other measures for reducing congestion. The chapter concludes with Section 11.5, which provides an overview of sustainable transport policy options for Sri Lanka.

11.1 Generic priorities for sustainable transport Sustainable transport is crucial for development as it provides access to jobs, health, education and other amenities, which determines the quality of life. Transport also provides physical access to resources and markets, which is essential for growth and poverty reduction. Poor transport policy could aggravate poverty, harm the environment, ignore the changing needs of users and overburden public finance. Several recent publications provide comprehensive expositions of sustainable transport and mobility, linked with the sustainomics framework and sustainable development triangle (SUMMA, 2003; World Bank, 1996c).

11.1.1 Key issues worldwide Some actions to make transport infrastructure development more sustainable include (World Bank, 1996c): (1) increasing access and affordability by increasing access of rural poor to 1

The valuable contributions of P. Meier to this chapter are gratefully acknowledged. Some parts of the chapter are based on material adapted from Munasinghe (1984b, 1990a) and Munasinghe and Meier (2003b).

355

356


markets and amenities, by expanding secondary and tertiary networks and improving public transport; (2) providing adequate maintenance in order to avoid increased costs of vehicle operation and higher long-run expenses borne by road agencies due to postponed repairs; (3) responding to customer needs in this era of rising incomes and rapidly changing markets, which generate demand for greater variety and higher quality services. (Priority should be given to greater safety, aesthetics and minimizing adverse health and environmental impacts.) (4) Adjusting to global trade patterns to move larger volumes of goods over longer distances, since bottlenecks in transport infrastructure hamper growth; and (5) coping with rapid motorization driven by rapidly expanding urban populations. In developing countries, ownership of vehicles is increasing at a faster rate than the amount of urban road space. Land-consuming urban structures have resulted in congested roads and slowmoving traffic, combined with a poorly maintained stock of vehicles causing immense pollution and long and costly journeys (especially for the poor).

11.1.2 Economic, environmental and social aspects The application of the sustainomics framework (especially the sustainable development triangle) to the transport sector provides useful insights (Munasinghe, 1992a; SUMMA, 2003; World Bank, 1996c). Figure 11.1 summarizes the main elements of sustainable transport.

ea

glo b

far

e on fz -of y de es nc tra da nt rg un me cha red ettle ice res serv nd

tra de -of al fz so on su urc e em ppl ing iss y m an ion ot d j su oriz ustpp ati inres on tim sio e n

economic and financial

safety asset maintenance efficient service operation efficient contract design efficient infrastructure investment

zone of synergy ecological and environmental

informal sector two-wheeled motorized vehicles

social and distributional

trade-off zone

Figure 11.1. Sustainable development triangle for transport. Source: adapted from Munasinghe (1992a) and World Bank (1996c).

11 Transport-sector applications

357

Economic and financial sustainability requires efficient use of resources and asset maintainance. Transport needs to be cost-effective and responsive to changing demands. Systematic economic appraisal of investments, appropriate price incentives and adequate financial and fiscal provisions for maintenance are essential. Suggestions for achieving economic sustainability include greater use of competitive market structures, higher efficiency in use, provision, financing and management of transport infrastructure and developing the strategic planning and system management capabilities to complement market forces. Environmental and ecological sustainability requires that external effects of transport be considered when decisions are made. Cost-effective technology and strategic actions such as land-use planning, demand management and incentive to use public transport through pricing for congestion and pollution are needed. Ways of achieving environmental sustainability include addressing health impacts, integrating environmental elements into project appraisal and developing an environmentally sensitive strategic framework. Social sustainability requires that the benefits of improved transport reach everyone. Greater attention should be paid to the role of the informal sector and non-motorized transport, the maintenance of rural transport facilities and the use of more labour-intensive techniques. We need to target the transport problems of the rural and urban poor, and protect them against adverse effects of changes in transport policies and programmes. All three dimensions of sustainable transport need to be considered in decision making. The government should remain as the competitive provider and custodian of environmental and social interests, become more involved in setting efficient charges for the use of publicly owned infrastructure, protect the poor and facilitate greater community participation in decision making. Transport policy could take on a more market-based approach, with the private sector providing, operating and financing more transport services and some infrastructure.

11.2 Health-damage costs of air pollution in Sri Lanka The impact of pollution on human health, especially of the poor, is important for social sustainability. This section analyses health damages due to transport-related air pollution in Sri Lanka. We review recent literature, estimate damage costs from local air emissions using the benefit transfer method and assess the health benefits of unleaded petrol.

11.2.1 Health effects Chandrasiri and Jayasinghe (1998) provide health-damage valuation related expressly to vehicular emissions in Sri Lanka. Despite limitations, it is the only study based on clinical data. Since the late 1990s there has been a steady increase in hospital admissions and deaths related to respiratory disease that closely tracks the increase in vehicle emissions of particulate matter (Figure 11.2). Figure 11.2 suggests that vehicle emissions increase faster than the hospital admissions/ deaths, with a likely lag effect. Most physicians interviewed stated that respiratory diseases

358

Sub-national and system applications 200

1991 = 100

180 160

vehicle particulate emissions

140

deaths

120

admissions

100 80

1991

1992

1993

1994

1995

1996

Figure 11.2. Vehicular particulate emissions (in Colombo) and hospital admissions/deaths (all Island) from respiratory diseases.

were related to vehicle emissions. This link was confirmed by a study of persons exposed to high emissions levels – trishaw drivers, traffic wardens and traffic police. While the emissions–illness causation is not proven, additional surveys of patients visiting doctors working in Colombo also provide more evidence. Senanayake et al. (1999) analysed hospital admissions of children for asthma attacks, and found significant correlation between the highest daily rates of wheezing requiring immediate nebulization and the highest daily maximum one-hour averages of SO2 and NOx (and similar correlation for the minimum rates). However, the link between asthma and air pollution is controversial – the UK Committee on the Medical Effects of Air Pollution (DoH, 1998) noted that the evidence does not support a causative role for outdoor air pollution, and opines that pollen and fungal spores are more likely to be influential. Indeed, in London, between 1976 and 1997, while asthma increased by 300%, emissions of air pollutants decreased by 180% (Glaister, Graham and Hoskins, 1999).

11.2.2 Valuation of local air emission damage Ideally, environmental damage costs should be measured directly (Munasinghe, 1992a). In this study, the benefit-transfer method is used – the basis of which is the extrapolation to Sri Lanka of damage valuations estimated elsewhere. While country-specific damage valuations are preferable, such data do not exist for Sri Lanka. Provided the limitations are recognized, the method can provide useful indicative valuations of likely damage (Freeman, 2000). This approach has been used in a number of recent developing country studies (Abeygunawardena et al., 1999; Meier, 2004), in Sri Lanka – in a study of the impacts of the 1996 power shortage (LIFE 1998) – and in the Environmental Impact Assessment of the Colombo–Katunayake Expressway (RDA, 1997).


359

Table 11.1 Damage estimates based on ADB benefit-transfer method and LIFE direct estimates Values given in US $/tonne ADB low

ADB high

Sri Lanka, 2000 Particulates SO2 NOx

258 53 81

478 106 116

Sri Lanka, 2020 Particulates SO2 NOx

1623 327 506

2779 654 697

a

LIFEa 483 825 334

Adjusted to 2000 using PPP.

Table 11.2 University of Moratuwa damage valuations

Car Motorcycle Three-wheeler Van Medium bus Large bus Medium lorry Large lorry a b

SL Rs/litrea

SL Rs/vehicle-kilometreb

0.57 0.56 0.62 0.65 0.71 0.79 0.71 0.79

0.06 0.01 0.02 0.07 0.14 0.2 0.14 0.23

Kumarage (1999), Table B4-2. Based on average fuel efficiencies.

The method requires the following steps (Abeygunawardena et al., 1999). (1) Specify the base year unit damage values (as US $/tonne per 1000 persons). For this purpose ADB uses the study by Rowe et al. (1995) for New York State. (2) Adjust price levels to the year 2000 using US GDP growth. (3) Multiply the values by the ratio of per capita GDP. In 2000, the per capita GDP in Sri Lanka, adjusted for purchase power parity (PPP), was US $3900 (WRI, 1999), and that of the USA was US $34 000. (4) Multiply the values by the estimated population resident within each radius. (5) For future years, adjust by the estimated population and GDP growth in each radius.

Application of this approach yields the values shown in Table 11.1. Values derived by LIFE (1998) for impacts of power generation in Sri Lanka are shown in the third column. Kumarage (1999) estimated damages in terms of SL Rs/litre for different vehicle types (Table 11.2). They show very little variation across vehicle types when expressed in

360


Table 11.3 Marginal damage costs Values in US $/tonne Power plant Large industry Small boilers and Ratio vehicle to power (high stack) [1] (medium stack) [2] vehicular [3] plant [4] = [3]/[1] Mumbai

PM10 SO2 NOx

234 51 20

1077 236 93

7963 1747 668

34 34 33

Shanghai PM10 SO2 NOx

161 36 11

502 112 33

5828 1295 385

36 36 35

Manila

PM10 SO2 NOx

345 61 24

1828 324 129

17 942 3183 1265

52 52 52

Bangkok PM10 SO2 NOx

828 147 57

2357 417 162

28 722 5087 1971

34 34 34

PM10 SO2 NOx

97 18 4

682 130 29

13 255 2522 560

136 140 140

Santiago PM10 SO2 NOx

692 132 35

4783 911 240

88 551 16 864 4445

128 127 127

Krakow

Source: Lvovsky et al. (2000), Table 1.5 (p. 16).

SL Rs/litre, but when converted to SL Rs/km travelled, the environmental damages show large variation, as expected. Chandrasiri and Jayasinghe (1998) estimated the value of health damages attributable to particulates in Colombo at between SL Rs67–160 million/yr, based on limited data of highly exposed occupational groups (traffic wardens, trishaw drivers, traffic policemen). World Bank (2000) assessed health damages in Colombo due to PM10 at US $30 million, using average ambient concentrations of 40–50 µg/m3. The ‘Six Cities Study’ Most health effect valuation studies in the USA and Europe relate to power-sector emissions (e.g. tall stacks in remote locations), which are difficult to use with the benefit-transfer method for vehicular emissions (at ground level in densely populated areas). One source of damage valuations is the ‘Six Cities Study’ (Lvovsky et al., 2000), which enables the benefit-transfer method to be applied to the health effects of vehicular emissions. The study derives damagecost estimates for vehicular emissions of PM10, SO2 and NOx in six cities (Table 11.3). The


361

Table 11.4 Unit health damages Values in US $/tonne per 1 000 000 population per US $1000 per capita income One-tonne change in emission of

High stack (power plants)

Medium stack (large industry)

Low stack (boilers and vehicles)

PM10 Range for six cities Average

20–54 42

63–348 214

736–6435 3114

SO2 Range for six cities Average

3–8 6

10–56 33

121–1037 487

NOx Range for six cities Average

1–3 2

3–13 9

29–236 123

Source: Lvovsky et al. (2000), Table 6-3 (p. 65).

values for the four Asian cities are 30–50 times greater than for power-plant emissions from high stacks (and even greater in the case of Krakow and Santiago). The marginal unit values shown in Table 11.4 provide useful guidance. Uncertainty is a major concern when determining the economically optimal level of renewable energy (Box 11.1). If we apply the lowest values in Table 11.4 to Colombo (with a population of 4.9 million and GDP/capita of US $4933), then the values compute to US $17 790/tonne for PM10, US $2924/tonne for SO2 and US $700/tonne for NOx, values, which is comparable to Manila. Table 11.5 summarizes all estimates, converted to Colombo for 2000. Considering only PM10, SO2 and NOx underestimates the total health damage. Glaister et al. (1999) estimated that the total damage cost for urban diesel emissions in the UK was 2.424p/km, of which 70% was due to to PM10 alone and 82% to the sum of PM10, SO2 and NOx. Lead There are no systematic health damage studies of lead in Sri Lanka, except for Chandrasiri and Jayasinghe (1998). However, we may draw on a vast international literature on the subject (Lovei, 1998). In the USA, the benefit–cost ratio of eliminating lead in petrol was estimated to be over 10 (USEPA, 1985), and Schwartz (1994) estimated health benefits of US $18.9 billion per year for reducing the US populations’ blood level by 1 µg/dlitre. Most governments in Asia have phased out leaded petrol. Table 11.6 shows the results of a study of lead levels in blood in Sri Lanka, compared with data from other countries (Awegoda, Perera and Mathhes, 1994). Despite differences in age, sample year, etc., lead levels are high in the most exposed groups compared with the control population. The general levels appear to be less than half of those in other large Asian cities. For Sri Lanka, we scale the estimate by ratio of population and ratio of PPP-adjusted GNP/capita. Then a reduction of lead concentration in blood of 1 µg/dlitre yields a benefit of

362


Box 11.1 The economically optimal level of renewable energy Decisions about implementing renewable-energy targets are pending in several countries as mandated market-share mechanisms are being considered. The standard methodology to estimate the economically optimal quantity of renewable energy is to derive a supply curve for renewable energy and then to set the renewables target at the quantity at which the costs of the marginal plant are exactly equal to the avoided costs (including the avoided environmental damage costs). In Figure 11.3, we assume that the cost of fossil-fuel generation (C), the externality value (VENV) and the supply curve (S) are all known. The optimal quantity of renewable energy is given by the intersection of the supply curve S with the avoided economic cost (including the value of the externality cost), i.e. by the point A. It follows that the economically optimal target is QN, which, if implemented by a system of tradable green certificates (TGCs), results in a TGC price equal to VENV. price S POUT

A

VENV

C = cost of fossil generation

QN

quantity

Figure 11.3. Optimizing the supply of renewable energy.

Clearly, if the actual damage cost were twice the assumed value of VENV, then a target set at QN would significantly underestimate the true economic optimum (and overestimate the optimum if the true damage cost were lower than the assumed value). This in turn has implications for the policy instrument used: if all quantities are known with certainty, then it matters little whether government sets a quantity target at QN or sets a price at POUT, since the result will be the same. But in the face of uncertainty, which may require a change in policy if new research findings reveal significantly higher (or lower) damage costs, adjusting a quantity target is likely to be much easier than adjusting a price (as vested interests defend the status quo); see Meier (2004). SL Rs19 billion (for 2000), or about 1.5% of GDP. Given year 2000 petrol consumption of 277 million litres/yr, this translates to SL Rs68.7/litre of petrol. Even if this estimate were reduced by a factor of 10, the benefits of unleaded petrol would still correspond to around Rs7/litre – a substantial benefit.


363

Table 11.5 Comparison of damage valuation estimates Values in US $/tonne Basis

Source

Colombo, 2000

PM10 as TSP Table 11.1 see text Table 11.1

17 790 14 232 258–478 8500 483 262

SO2 Six Cities Study, low value of range ADB benefit-transfer method LIFE University of Moratuwa

see text Table 11.1 Table 11.1

2924 53–106 825 447

NOx Six Cities Study, low value of range ADB benefit-transfer method LIFE University of Moratuwa

see text Table 11.1 Table 11.1

700 506–697 334 180

a

Particulates Six Cities Study, low value of range ADB benefit-transfer method RDAb, CKE environmental assessment LIFE University of Moratuwa

a

The Six Cities Study gives PM10 health damage costs; the others are for total particulate matter. For ambient air quality, the Six Cities Study uses a PM10/TSP ratio of 0.55; however, emissions of PM10 are 0.8 of the TSP emission factor for diesel vehicles and 0.9 of the TSP emission factor for petrol vehicles. The share of PM10 in total TSP from typical power plant stacks is about 0.6. b Road Development Authority.

Table 11.6 Average lead levels in blood Sri Lanka (Colombo)

Mean (µg/dl)

School children (4–5 years) Motorcycle riders Street vendors Three-wheeler drivers Traffic police Adult control group

5 12 13 15 53 9

Other locations Bangkok Manila Jakarta

40 20 15

Sources: International data from Lovei (1998); Sri Lanka data from Awegoda et al. (1994).

364


11.3 Traffic congestion – economic and environmental sustainability Traffic congestion, especially in the rapidly growing major cities of developing countries, is imposing increasing economic and environmental costs. Traditional methods of reducing congestion have failed, particularly on the supply side – e.g. road expansion only provides short-term relief and is limited by tight fiscal, physical and environmental constraints. However, demand side options like pricing offer better a long-term solution – e.g. the successful pricing scheme in Singapore, one of the few large Asian cities free of major road congestion (Jayaweera, 1999). Most traffic entering Colombo uses seven main radial roads, which all connect to the central business district (CBD). These roads all exhibit very strong peak-hour traffic; Figure 11.4 shows typical inbound and outbound patterns for the A3 route. Congestion occurs when an additional vehicle entering a road segment causes the normal speed of other vehicles to decrease, thereby imposing costs not only on that additional vehicle, but also on all vehicles using that road segment (Jayaweera, 1999). Based on a definition of congestion as occurring whenever average speeds of 30 km/hr cannot be maintained, the Colombo Urban Transport Study (CUTS) estimates the costs of congestion at SL Rs11 billion/yr, which is equivalent to 1.5% of the 1996 GDP. This value is likely to rise in the absence of policy reforms. Already average speeds in the Greater Colombo Metropolitan Region (GCMR) have dropped to about 22 km/hr, and range from 10–15 km/hr in the centre to around 45 km/hr at the periphery of the GCMR. Sharp reductions in road speed result in significant increases in air emissions, because fuel efficiency decreases non-linearly with speed (particularly for buses and trucks) – see the 2001 traffic data on the Colombo–Ratnapura road given in Figure 11.5. Jayaweera (1999) estimated the optimal congestion toll in Colombo by setting it equal to the difference between marginal social cost and average private cost. We extend this microeconomic work to calculate aggregate economic effects and estimate related environmental benefits.

average daily traffic (1000 vehicles)

15

inbound outbound

10

5

0 :0

0

Figure 11.4. Hourly mean daily traffic for the A3 (Peliyagoda–Puttalam).

22

0

:0 20

0

:0 18

0

:0

:0

16

0

14

0

:0 12

0

:0 10

0

:0 08

0

:0 06

0

:0 04

:0

:0 00

02

0

0


fuel efficiency (litres/100 km)

80

365

truck (Tata 2-axle, diesel) bus (Tata 432, diesel)

60

40

20

2200cc diesel van 1499cc car (ToyotaCorolla)

0

10

20 speed (km/hr)

30

40

purchase price, constant 1982 prices (1000 Rs)

Figure 11.5. Fuel efficiency survey for typical vehicles. 500

diesel

400

300 dual-purpose 200 petrol

100

motorcycle 0

1970

1973

1976

1979

1982

1985

1988

1991

1994

1997

Figure 11.6. Vehicle prices, in constant 1982 rupees. Source: Sri Lanka customs. GDP deflator from Central Bank.

11.3.1 Price elasticities In the following, we examine the influence of prices on decisions of road users (see also Chapter 14). The initial choice of vehicle (e.g. diesel or petrol) is likely to depend on purchase price and expected cost of operation (especially fuel price). Next, the pattern of vehicle use will depend mainly on fuel prices. Tax rates play as much a role in these decisions as world oil prices and CIF prices of automobiles. Customs and excise duties on vehicle imports show wide variations across different vehicle types, with complex and fastchanging exemptions and concessions (Chandrasiri, 1999). Vehicles are not manufactured in Sri Lanka (although some are assembled), so the entire demand is met by imports, of which only 25% are new vehicles (Chandrasiri, 1999). The typical passenger car import is a 2–3-year-old, reconditioned Japanese vehicle. In Figure 11.6

366


Table 11.7 Comparison of the diesel and petrol vehicle price for the Toyota model RAV4 Cost in rupees Petrol Costs at purchase CIF 1 800 000 Import duty 267 000 Defence levy 108 489 Excise duty 254 400 GST 198 721 Stamp duty 21 380 Total tax 850 092 Total CIF + tax 2 649 992 Tax as percentage of total price 32% Registration 3500 Diesel tax Luxury taxa Annual fuel cost km/yr km/litre litre/yr Price/litre Annual fuel cost

15 000 10 1500 50 75 000

Diesel 2 200 000 534 000 217 000 508 800 397 400 42 800 1 700 000 3 900 000 44% 6500 10 000 50 000 15 000 10 1500 21.50 32 250

a

Luxury tax falls by SL Rs10 000/yr, reaching zero in the sixth year. Figures are tabulated for taxes and typical prices as of April, 2001.

we show the average nominal price, ex-customs, for four main types of passenger vehicle, expressed in constant 1982 rupees – most of the price variation reflects changes in taxation. Table 11.7 shows a comparison of the taxes levied on diesel and petrol cars, using the same Toyota model differing only by type of engine (3-year-old reconditioned vehicles). The (absolute) tax on the diesel vehicle at the time of purchase is seen to be double that of the petrol-powered car, though as percentages of the initial cost the tax burden is comparable. Asian price elasticities of aggregate transportation fuel demand are shown in Table 11.8. However, many of the Sri Lankan estimates are limited to the period 1970–1985, and do not properly capture the major changes in road transport consequent to liberalization of the economy in 1977. There are some problems. For petrol-demand studies, defining the independent variable as consumption per vehicle fails to consider rapid changes in the vehicle mix – mainly the significant growth in motorcycles (whose fuel demand per vehicle is a small fraction of that of automobiles). For example, McRae (1994) did not cover motorcycles and


367

Table 11.8 Estimates of own-price elasticities of demand for transport fuels in Asia

Sri Lanka de Silva (1989) Samaraweera (1989) Ranasinghe (1989) Meier et al. (1997) McRae (1994) Jayaweera (1999)

Year

Petrol

Diesel

1970–1985 1970–1985 1970–1985 1973–1991

− 0.55 − 0.387 − 0.508 − 1.14 (long run) − 0.334 (short run) − 0.337 − 0.163 (long run) − 0.115 (short run)

− 1.21 − 0.26 − 0.034

1973–1987

Other countries Philippinesa Thailanda Malaysiaa S. Koreaa S. Koreaa

1973–1987 1973–1987 1973–1987 1973–1987 1973–1997

Indonesiaa Indiaa Taiwana Taiwanc

1973–1987 1973–1987 1973–1987 1954–1985

Taiwand

1973–1992

− 0.339 (long run) − 0.154 (short run)

− 0.391 − 0.304 − 0.125 − 0.496 − 0.866 (long run)b − 0.385 (short run)b − 0.197 − 0.321 +0.024 − 1.362 (long run) − 0.245 (short run) − 0.519 (long run)b − 0.124 (short run)b

Dependent variable is consumption per vehicle in all Sri Lanka studies. a Source: McRae (1994). b Demand for petrol and diesel are taken together (see discussion in the text). c Source: Garbacz (1989). d Source: Banaszak et al. (1999).

three-wheelers. Some studies add a variable for vehicles per capita, whose elasticity is almost always strongly negative – as vehicles per capita will reduce utilization (McRae, 1994). For Sri Lanka, only Meier, Munasinghe and Siyambalapitiya (1997) includes the fraction of motorcycles in the vehicle mix as a variable (with a corresponding elasticity of − 0.17). Among Asian studies, the most rigorously specified is that of Garbacz (1989) for Taiwan. However, even this study was unable to include vehicle price variables. Both Taiwan and Sri Lanka studies (Meier et al., 1997) show similar results for both long- and short-run elasticities (Table 11.8), and agree with the average value of −1.05 for long-run elasticity across developing countries; see Dahl and Sterner (1991).

368


Since petrol and diesel are partial substitutes, their cross-price elasticities are important. Therefore, price and income elasticities must be estimated simultaneously, either by (1) combining petrol and diesel consumption and using a price variable that is the weighted diesel and petrol price or (2) simultaneously estimating the two equations. The former approach was taken by Banaszak, Chakravorty and Ljeung (1999) for Taiwan and S. Korea, and the latter by Chandrasiri (1999) for Sri Lanka. However, the consensus view in the international literature favours the ‘lagged endogenous model’, which (for petrol demand) has the following functional form used by Meier et al. (1997) and Jayaweera (1999): QðgÞt ¼ kQðgÞlt1 Yt PðgÞt PðdÞt Vt ;

(11:1)

where Q(g)t = petrol demand (sales/number of vehicles) at time t, P(g)t = petrol price at time t, P(d)t = diesel price at time t, k = constant, Y = per capita GDP (at constant prices), V = vehicle mix variable (for example, fraction of motorcycles), λ = lag coefficient, α = income elasticity, β = short-run own-price elasticity, μ = cross-price elasticity for diesel, γ = vehicle mix coefficient. The long-run price elasticity may now be calculated; it is given by ¼

: ð1 lÞ

(11:2)

For the petrol equation, the relevant vehicle-mix variable is the fraction of motorcycles, while, for the diesel equation, the fraction of light diesel vehicles is the relevant variable. The results in Table 11.9 compare the OLS (ordinary least squares) and SURE (seemingly unrelated regression equations) estimates for the time series 1968–2000. In the SURE method, equations are estimated simultaneously to avoid problems when the error term across equations are correlated, which is the case in fuel-demand equations linked by cross-price elasticities (Lutkepohl, 1991). The lag variables have the correct sign and magnitude, and the results of SURE and OLS are surprisingly close. The vehicle fleet variables (fractions of motorcycles in petrol and heavy vehicles in diesel) are significant and have the correct sign. The diesel own-price elasticity is not significant. Taking into account the wide variation in values reported in the literature, we summarize the elasticity values in Table 11.10. A different approach (requiring more detailed data) is to derive vehicle-kilometre elasticities. They measure the change in vehicle-kilometres travelled in response to changes in total (private) vehicle operating costs (including fuel, lubricants and maintenance) by different vehicle class. The OLS results estimated in log-linear from 1988–2000 are shown in Table 11.11 and are used in the analysis of congestion tolls presented below.


369

Table 11.9 Comparison of SURE and OLS estimates Petrol

Diesel

Variable

OLS

SURE

OLS

SURE

CNST

0.412 (0.226) − 0.151 (1.82) 0.091 (1.02) − 0.059 (0.317) 0.704 (6.38) − 0.1 (2.18)

0.365 (0.207) − 0.155 (1.9) 0.089 (1.01) − 0.054 (0.3) 0.693 (6.35) − 0.099 (2.18)

1.94 (2) 0.045 (0.833) − 0.07 (1.18) − 0.144 (1.96) 0.765 (7.46)

2.08 (2.21) 0.039 (0.74) − 0.63 (1.06) − 0.156 (2.17) 0.758 (7.62)

− 0.151 (1.37) 0.979

− 0.168 (1.54) 0.979

Petrol price Diesel price Tax rates Lag effect Fraction of motorcycles Fraction of heavy-duty vehicles R2

0.962

0.962

Statistically significant values are shown in bold; the t-value is given in parentheses.

Table 11.10 Short- and long-run price elasticities

Own-price

short-run long-run

Cross-price

Petrol

Diesel

− 0.16 − 0.51 0.09

− 0.07 − 0.29 0.05

Statistically significant values given in bold.

Table 11.11 Vehicle-kilometre elasticities Vehicle category

Elasticity

Car (diesel/petrol) Light truck (diesel) Medium truck (diesel) Heavy truck (diesel) Medium bus (diesel) Large bus (diesel) Motorcycle (petrol)

− 0.349 − 0.23 − 0.443 − 0.26 − 0.15 − 0.13 − 0.462

Estimates by D. Jayaweera (personal communication).

370


Table 11.12 Estimated price elasticities − 0.08 − 0.07 − 0.04

Public bus Private bus Rail

Source: Dheerasinghe and Jayaweera (1997).

S0

speed

cost S1

Smax

S1

S0 V1

Smax

Vmax

traffic flow

V1

(a)

traffic flow

Vmax

(b)

Figure 11.7. Speed and cost versus traffic.

Finally, Table 11.12 shows low own-price and negative cross-price elasticities of public transport, suggesting that the different modes are complements rather than substitutes (Dheerasinghe and Jayaweera, 1997). Rail usage increased significantly from 7% of personkilometre to 9%, after the bus fare increases of 2000, although prior bus fare increases (in constant terms) in 1974, 1980 and 1987 had little effect.

11.3.2 Theoretical model Figure 11.7 illustrates the fundamental relationship between speed, cost and traffic flow. In Figure 11.7(a), starting at low flows (V1) and an empty road, the speed is given by S1. Speeds decline as additional vehicles join the flow, reaching Smax at flow Vmax. Beyond this point, additional vehicles result in a reduction in flow, reaching near-zero flow and speed (S0). Figure 11.7(b) shows the corresponding ‘average private cost’ curve faced by a motorist. The term ‘average private cost’ is used to stress the difference between private and social costs. As speeds decline, private costs to the motorist increase (because time per trip, and value of time per trip, rise, while fuel efficiency decreases). As more vehicles enter the road beyond Vmax, costs continue to increase (tending to infinity with total gridlock). We


371 MSC

A

P* PX PY P0

APC

demand (peak)

demand (off-peak) V0

V* VX

Figure 11.8. Optimal pricing and congestion.

may ignore the (upper) backward bending part of the curve, because optimal solutions always lie on the lower part. Traffic congestion occurs because the marginal user considers only his or her private costs when making a decision regarding a particular trip at a particular time, ignoring any costs imposed on others. In Figure 11.8, up to some given traffic volume V0 (i.e. the capacity of the road), the private cost is (roughly) constant, P0. As traffic increases beyond V0, speeds fall and the individual’s private costs increase – because covering a given distance requires more time and fuel efficiency is lower as speeds decrease (higher fuel costs). Therefore, beyond V0, the private cost (APC) curve slopes upward, intersecting the demand curve at point A (VX, PX). However, beyond V0 the marginal user imposes these same externalities on the other road users as well, as the decrease in speed is experienced by all. The marginal social cost (MSC) curve therefore lies higher than the private cost (APC). Thus the societal optimal traffic volume is at V*, P* – where the (peak period) demand curve intersects MSC (rather than APC). Welfare theory argues for a ‘Pigouvian’ tax (see Section 3.2.2) on the use of congested roads in the amount Δ = P* − PY, at which point the private users’ total cost (private cost plus tax) exactly equals the social cost (also equal to the marginal social benefit represented by the demand curve). The off-peak demand curve lies far to the left of the peak demand curve, and the optimal toll would be very small or zero (e.g. at night).

11.3.3 Estimating the value of time Time savings provide the greatest economic benefits of reducing traffic congestion. People would pay more to avoid time delays, depending on their personal opportunity cost of time. Since detailed income data are unavailable for road users in Sri Lanka, average salary is used. Employers would place an opportunity cost on driver’s time that is equal to gross salary. For bus riders (largely salaried), road congestion and longer commute times will reduce leisure time (or sleep). While there is no direct measure of the value of leisure time,

372


Table 11.13 Average monthly income of drivers and passengers SL Rs/month Car passenger Van passenger Bus passenger Car driver Van driver Bus driver Truck driver

21 000 16 500 3800 4700 5040 10 080 11 280

Source: University of Moratuwa, Origin–Destination Survey, May, 1998.

Table 11.14 Value of time Value of time Ratio to value for Ratio based (SL Rs/hr) car passenger only on salary Car passenger Van passenger Bus passenger Car driver Van driver Bus driver Truck driver

26.5 21.4 8.8 16.8 13 16.4 19.3

1 0.81 0.33 0.63 0.49 0.62 0.73

1 0.79 0.18 0.22 0.24 0.48 0.54

Source: Jayaweera (1999), Tables 5.8 and 5.2.

we may assume it would be related to income (Munasinghe, 1980c). Table 11.13 shows average monthly incomes of road users, as a guide to relative opportunity cost of time. In the following, we use the value of car passenger time as the exogenous variable, and link other users, value by the proportions implied in Table 11.13. Escalating the passenger salary by 5% (real GDP growth rate in the reference case), the 2001 value is SL Rs24 310/ month, or SL Rs138/hr – (22 working days at 8 hr/day). The value of time is also related to trip purpose. The share of work commuting, education and business is 43%, 21% and 16% among the main peak period road users, respectively. Jayaweera (1999) estimates lower values of time (Table 11.14). The value for car passengers is only SL Rs26.5/hr (SL Rs30/hr at 2000 prices). The greater value (SL Rs138/hr) may be justified for the expressway/A30 corridor, since the proportion of higher-valued business trips is likely to be more than for in-city average values. However, in Section 11.3.5, we use Jayaweera’s figures for a more conservative estimate of benefits. The average value of time for goods vehicles was taken as SL Rs150/hr (plus driver’s time as noted above), based on Jayaweera (1999).


373

Table 11.15 Proposed tolls (daily equivalent) Jayaweera Colombo Council Car Light truck Medium truck Heavy truck Medium bus Light bus Motorcycle

25 20 20 40 0 0 10

8 8 8 8

8

45

average speed (miles/hr)

40 with toll

35

30

25 no toll 0

0

:0 22

0

:0

0

:0

20

18

0

:0 16

0

:0

0

:0

14

12

0

:0 10

0

:0

0

:0

08

06

0

:0

:0

04

:0 00

02

0

20

Figure 11.9. Average speed at various times of day (base-case tolls, A3).

11.3.4 Impact of a congestion toll Table 11.15 shows Jayaweera’s graduated toll proposal and the flat rate proposal of the Colombo Municipal Council. The former, which includes differences in externality costs by vehicle class, is used as our reference case. The response to a toll may not conform to estimates of past responses to changes in volatile organic compound (VOC) emissions. Figure 11.9 shows the predicted changes in road speeds in response to a toll, based on the elasticities of Table 11.11. Meier and Munasinghe (2003) describe the detailed model used to relate vehicle speeds to traffic volume (which itself depends on the toll and price elasticity). The corresponding pattern of avoided trips is shown in Figure 11.10. A very minor correction is not shown in the figure – one additional bus trip for every 40 avoided motorcycle or car trips, which has little impact.

374


avoided daily traffic by hour

1200

motorcycle heavy truck

1000

medium truck 800 600

vans

400 cars

200

0 :0

0

22

0

:0 20

0

:0 18

0

:0

:0

16

0 :0

14

0 :0

12

0

0

:0

10

08

0

:0 06

0

:0 04

:0 02

00

:0

0

0

Figure 11.10. Impact of congestion toll on speed during the day (A3, outbound).

cost/trip

C

Y

X

demand

NT

N0

number of trips

Figure 11.11. Welfare losses.

11.3.5 Economic analysis The calculation of costs and benefits is straightforward, including welfare losses that depend upon behavioural responses to the toll. For passenger trips (cars, vans and motorcycles), the potential responses are: (1) make the trip at the usual hour and pay the toll; (2) forgo the trip; (3) take public transport (bus); and (4) avoid the toll by entering the city before 7 am and leaving after 8 pm (since toll stickers must be displayed for in-city driving, this response is unlikely and ignored in the model). Figure 11.11 shows the loss of consumer surplus due to the reduction in number of trips induced by the toll. The loss of surplus is the area Y + X, where ½N0 NT ; 2 Y ¼ NT ; X¼


375

Table 11.16 Physical impacts of the congestion charge Toll = SL Rs75

Toll = SL Rs25

Low elasticitya High elasticityb Low elasticity High elasticity −19.1 −15 −18.3 −18.3 0.5 1 −25.7 −10.7

−3.9 −3.1 −3.7 −3.9 0.1 0.3 −5.6 −2.2

−7.7 −6.1 −7.2 −7.6 0.2 0.5 −10.8 −4.3

Environment (emission reductions) GHGs (lifetime) 1000 tonnes 17

33

6.4

12.8

Year 2010 reductions PM10 (tonnes) SO2 (tonnes) NOx (tonnes)

2 13 75

Car (%) Light truck (%) Medium truck (%) Heavy truck (%) Medium bus (%) Large bus (%) Motorcycle (%) Total (%)

a b

−10.1 −7.9 −9.7 −9.7 0.3 0.6 −14 −5.7

1 7 39

0 3 15

1 5 29

Low elasticity = values as in Table 11.11. High elasticity = 2 × vehicle operating cost values.

and where τ is the daily toll, and N0 and NT are the numbers of trips before and after the toll. Thus, Y is the toll revenue collected by the government and X is the deadweight loss. This is an approximation, since private travellers may experience further inconvenience and loss of utility when shifting to public transport. Table 11.16 shows the physical environmental impacts as a function of the toll and elasticity. Based on historical VOC (low) elasticity, the total traffic reduction in response to a Rs25 daily toll will be only 2.2%, with 3.9% and 5.6% declines in car and motorcycle traffic, respectively. The decline in air emissions is also small. The reference case costs and benefits, under the Jayaweera toll, is shown in Table 11.17. The big winners in Table 11.17 are (low-income) bus users – because of large numbers of passengers, aggregate time savings and economic benefits are greater. If deadweight losses (loss of surplus for those shifting to less convenient transport modes) are excluded, car passengers break even, because their time and fuel savings are about equal to toll payments. With deadweight losses, the net impact on car users is negative. For trucks, the net impact is always positive, so there is no basis for raising commodity prices. Figure 11.12 shows results as net present values over 20 years (10% discount rate). Thus, road pricing via a congestion toll has a major positive economic impact. Although environmental benefits amount to under 1% of economic benefits, the toll still yields a win–win outcome.

376


Table 11.17 Impact of the Jayaweera toll in year 2010 Road users Low Medium High Environment income income income Freight (bus) (motorcycle) (car) (truck) Govt Others Total Local Global Total [1] Time savings 578 Tolls 0 Petrol fuel tax Diesel fuel tax 5 Diesel savings 87 Petrol savings Deadweight losses 0 Admin. costs Commissions Environment PM10 SO2 NOx GHG Total

[2]

[3]

[4]

21 −99 0

489 −1280 8 1

354 −593

0 −7

19 −56

−85

671

2 47

−819

[5] [6]

[7] [8]

−30 −197 197

1442 0 0 0 134 20 −90 −30 −197

1728 197

0 0 0 0 1278

1972 −8 −9

−27

−217

[9]

[10] 1442 0 0 0 134 20 −90 −30 −197

2 2 3 7

1 1

2 2 3 1 1286

15

Rs billion

10 5 0 –5

nv )

v. to

tal

(+ e

. nv

en

le

ba l

gl o

rs

tal lo

ca

to

he ot

go vt

in c. bu sin es s

. nc

gh hi

.i ed

m

lo

w

in

c.

–10

Figure 11.12. Congestion toll winners and losers (net present value over 20 years).

Figure 11.13 shows a sensitivity analysis of net economic benefits to the toll (for 2001), scaled by the passenger car charge. The optimum passenger car toll is about SL Rs35/day, which is higher than the value of SL Rs25 determined by Jayaweera based on microeconomic theory – because buses are exempted, so the toll for remaining vehicles has to

net economic benefits (NPV, Rs billion)


377

60 40 20 0 –20 –40

0

20

40 60 congestion charge (Rs/day)

80

Figure 11.13. Net present value (NPV) of benefits (Rs billion) versus congestion charge (Rs/day/ passenger car).

be increased to achieve same overall congestion benefit. Thus, results of this aggregate (macro) model are consistent with microeconomic theory.

11.4 Other options for reducing traffic congestion Meier and Munasinghe (2003) examine several other options to reduce traffic congestion in the Colombo area: (a) a new expressway from the centre of Colombo to the Katunayake airport; (b) railway electrification; (c) reintroduction of school buses; and (d) dry container port, designed to reduce congestion in both the main northbound artery and Colombo Port. Each analysis uses the same methodology as described in Section 11.3.

11.4.1 Katunayake airport expressway The present A3 road to the airport is the most heavily travelled in Sri Lanka, with average daily traffic (ADT) of 200 000 near Colombo (about 1% of all vehicle-kilometres in the country). A 25 km, four-lane, limited access expressway to link downtown Colombo with the Katunayake airport (the Colombo–Katunayake Expressway, or CKE) has been discussed for almost two decades. Due to delays and environmental objections (RDA, 1997; Sivagnasothy and McCauley, 2000), cost estimates have risen from SL Rs5 billion in 1995 to over Rs13 billion in 2000, when construction began. Meanwhile, the air pollution due to traffic congestion on the A3 road will continue to worsen. Insights derived from the analysis of the expressway project will help in studying other highway proposals, such as the Southern Highway (linking Colombo to Matara on the South Coast) and the Outer Circular Highway (Colombo orbital road, also connecting to the airport expressway).

378

Sub-national and system applications K

D T2 D T1 MCA3

PA3

E

B

ΔC A

H

F

G

I

QT1

QT2

PEX

QA3

QA3E QE

ΔG1

ΔG2

Figure 11.14. Estimating consumer surplus changes.

Theory The economic benefits of the new road are calculated in our model, as the change in consumer surplus – for both new road users and old road users (who suffer less congestion). Consider the demand curve DT1 depicted in Figure 11.14. Before the project, users of the A3 experience costs of PA3 at traffic volume QA3 (given by the intersection of the demand curve and the marginal cost curve MCA3). Once the project is built, some vehicles (QE) will elect to use the expressway, leaving QA3E on the original road. Road users will experience lower costs, PEX, due to fuel and time savings ΔC = PA3 – PEX. However, at the new lower cost PEX, the total travel demand increases from QA3 to QT1, the difference ΔG1 being the induced traffic (whose quantum is a function of the demand elasticity, i.e. of the slope of the line DT1). The benefit is the change in consumer surplus, or increase from the original area KBE to KBAHFGE – assuming a linear demand curve. Thus: DB1 ¼ KBAHFGE KBE ¼ ABEF þ EFG ¼ DC QA3 þ 0:5DC DG1 :

(11:3)

There will also be an outward shift in the demand curve, shown in Figure 11.14 as DT2. This intersects price PEX at I, leading to an increase in traffic to QT2 and a larger consumer surplus increase from KBE to KBAHFGIE: DB2 ¼ KBAHFGIE KBE ¼ ABEF þ EFGI ¼ DC QA3 þ 0:5DC DG2 :

(11:4)


379

Table 11.18 Tolls proposed by Board of Investment (one-way toll) Vehicle type

SL Rs

Car Van Bus Large bus Delivery van Truck Container truck

65 95 140 180 195 390 650

However, at the higher level of traffic within the corridor, there will be increased congestion outside the corridor, particularly on the access roads to the expressway interchanges. This externality, say ΔC*, would reduce the level of benefits. In this study we assume that this externality exactly offsets shifts in the demand curve induced by the expressway (ΔC* = ΔB2 − ΔB1), so that benefits are given by ΔB1 (in Equation (11.4)). Results A large range of traffic forecasts exist (Kumarage et al., 2000; University of Moratuwa, 2000). Typical 2025 estimates of daily vehicle-kilometres on the expressway range from 325 000 to 747 000, and on the A3 from 836 500 to 1 708 000, with toll revenues varying from Rs1.7 million/day to Rs4.1 million/day – based upon the toll structure shown in Table 11.18. Truck charges are high, but car tolls approximate potential time savings. Table 11.19 shows values of environmental impacts. For air pollution, we use our estimates, since the CKE Environmental Impact Statement values are overstated. The 20-year net present value (NPV) of costs and benefits is shown in Table 11.20. Bus passengers are assumed to benefit only from time savings (since fuel savings would accrue to bus owners and offset tolls). Although motorcyclists would be banned from the expressway, they benefit from both time and fuel savings from the less congested A3. Time savings of bus, van and truck drivers accrue to the owners of these vehicles. Clearly, air emission benefits outweigh the non-air costs, and inclusion of the environmental benefits simply makes a good project better. As expected, freight is the single largest beneficiary. Low-income road users (including bus passengers and pedestrians suffering fatalities and serious injuries) derive greater benefit than car passengers. Toll income (even at SL Rs50) would more than cover the operation and maintenance costs of the Road Development Authority (RDA), but still leave a significant funding gap for debt service.

11.4.2 Railway electrification The government has been studying options for electrifying suburban rail in Colombo for several decades, including possible private-sector investment. The section of railway line

380


Table 11.19 Valuation of local environmental impacts NPV (SL Rs million) Sigvagnasothy and McCauley CKE-EIS study Updated to 2000 (2000) (1991 prices) (1995 prices) for our studya Conversion of agricultural landb −42 Noise and air pollutionc −41 Noise pollutiond Air pollution Reduced biodiversity and lagoon area Water pollution and fishery losses −8 Reduction in road accidentse Conversion of non-agric. lands −660 Loss of structures −598 Increased flooding

−29 1377 −83 112

−70

−84 −82 −40 see text −118 −16 159 −1331 −1206 −99

Negative numbers = costs; positive numbers = benefits. a GDP deflator from Central Bank Annual Report. b Opportunity costs of lost agricultural production. c Estimated change in property values. d Assuming a 10% loss of property value due to more noise. e The CKE-EIS figures on an annual basis. These are converted to NPVs over 25 years at 12% discount rate.

proposed for electrification between Colombo Fort and Veyangoda is part of the main line. The benefits of railway electrification are as follows. (1) Travel time savings to former diesel multiple unit (DMU) passengers, because electric multiple units (EMU) have higher travel speeds and greater operational frequency. The total time saving (DMU minus EMU passenger hours) is multiplied by the value of time taken as SL Rs10.83/hr (Kumarage, 1999). This value is assumed to increase in real terms with the increase in per capita income assumed for each scenario. (2) Travel time savings to former bus passengers. Total time savings (bus minus EMU passenger hours) are multiplied by the same value of time. (3) Vehicle operating cost savings from diversion of former bus passengers to EMU, because lower demand for passengers would lead to fewer buses on the congested road network. The operational economic cost of these buses is taken as SL Rs18.80/km, and each bus is assumed to carry 50 passengers (Ministry of Transport, 1999). (4) Lower air emission damage from reduced use of buses. (5) Reduced air pollution due to electrification. We assume that the incremental electricity required for EMU operation is based on oil or coal, and that roughly the same amount of fossil fuel would need to be used as is presently used by the DMU. The benefit arises because DMU emissions occur at trackside in densely populated areas, whereas power generation is at remote plants with tall stacks. Typical health damages for ground-level and high-stack emissions are in the ratio of 3114/42 for PM10, 487/6 for SO2 and 123/2 for NOx (Lvovsky et al., 2000). We apply these ratios to the emissions from 4.6 million litres of fuel used by DMU. (6) Savings from accident costs due to reduced bus travel. Accident costs are SL Rs0.08/passengerkilometre for road transport (Kumarage, 1999) and SL Rs0.04/passenger-kilometre for rail.

b

a

−8589

2922 −10 372 −1140

Road Development Authority. Ceylon Petroleum Corporation.

Environment Non-air impacts Air emissions PM10 SO2 NOx Carbon Total

Tolls Construction O&M costs Time savings Diesel fuel tax Petrol fuel tax Diesel savings Petrol savings Fuel imports Port distribution margins Road accidents

RDA

a

13 264

1681 −0

14 505

−2922

Freight (truck)

4180

115

4065

Low income (bus)

1460

88

1371

Med. income (motorcycle)

Road users

Table 11.20 Airport expressway: distribution of costs and benefits NPV (Rs million) at 2000 price levels

2746

536

3051

−841

High income (car)

−778

−419 −359

Govt

0

419 359 −1681 −624 1472 55

CPC

b

0 0 0 0 12 281

−841 −10 372 −1140 22 992 0 0 0 0 1472 55 115

Total

333

147 253 290

−357

Local

574 574

Global

Environment

147 253 290 574 13 188

−357

−841 −10 372 −1140 22 992 0 0 0 0 1472 55 115

Total

382


Rs billion

5

0

–5

v) en (+

to

tal

al ob gl

lo

ca

le

en

nv

v.

.

tal to

ay ilw

vt ra

go

ra pe so

bu

ro

ad

us

to

er

s

rs

–10

Figure 11.15. Winners and losers: railway electrification.

Railway electrification is found to be uneconomic (Figure 11.15), with an NPVof economic loss around SL Rs3 billion. While there are clear benefits to road congestion and reduced vehicle operating costs, these are insufficient to warrant the high capital costs of electrification. The environmental benefits are positive but small, and are insufficient to offset the large economic loss. Using a 30-year time horizon appropriate for such projects, the switching values of discount rate (where NPV changes from negative to positive) are 4% and 3.5%, respectively, with and without environmental benefits. They are far below the opportunity cost of capital (6–10%). Our analysis agrees with previous studies showing that electrification of the northern commuter line is uneconomic. We further show that environmental benefits are very small, and therefore that, electrification of railways is a very expensive method of reducing local air emissions.

11.4.3 Dry container port The Colombo Port plays a economic key role, and the trans-shipment traffic is highly profitable. However, there are major harbour space constraints that prevent large-scale expansion. Thus, efficient operation of the port is vital. Colombo competes with Indian ports to become the regional hub for container operators and consortia. At the southernmost point of South Asia, Colombo has a unique geographical advantage for trans-shipment operations, which the government wishes to exploit. Domestic containers spend too much time in the port, thereby occupying space that could be given to the more profitable trans-shipment traffic. This situation will worsen with the growth of domestic container traffic. To reduce dwell time and free up port capacity, a port inland clearance depot (PICD) has been proposed for all domestic containers.


383

45

average speed (km/hr)

40

35

with PICD

30

25 baseline 0 :0 0 16 :0 0 18 :0 0 20 :0 0 22 :0 0 14

0

:0 12

0

:0 10

0

:0 08

0

:0 06

0

:0 04

:0

:0 00

02

0

20

Figure 11.16. Impact of the PICD on speeds on the A3 (2001).

The problems of port congestion are aggravated by traffic problems in Colombo. As domestic container traffic has grown, more articulated lorries move containers to their private inland depots, many of which are located north of Colombo on the A3 radial road. This has significantly worsened congestion (see Figure 11.3). Heavy lorries (mainly container vehicles) account for 5% of vehicles, but 8% of road capacity. While, a full cost–benefit analysis of port operations goes beyond the scope of this study, the benefits of the proposed PICD may be identified as: (1) increased throughput of transshipment container traffic; (2) deferral of the construction of a new port, or major new expansions to increase port capacity; and (3) cost savings to private operators due to reduction in dwell time in the port. The model presented earlier for evaluating congestion pricing is used to estimate benefits from reduced road congestion on the A3 (as container traffic is diverted to the railway) and the resulting environmental benefits (reduced emissions from container trucks and other road vehicles due to higher average speeds). Removal of this traffic from the A3 would improve average speeds by 3–4 km/hr during peak hours (see Figure 11.16). Table 11.21 shows the distribution of costs and benefits. The analysis considers both the A3 and Kandy roads (the two radial roads with the heaviest container lorry traffic, having trip lengths of 12 km and 6 km from Colombo, respectively). It is assumed that the PICD would reduce heavy lorry traffic on the A3 by 75%, and on the Kandy Road by 50%. The residence time of rail shipment is conservatively assumed to be 50% that of road shipment. PICD costs incurred by the railways and port are recovered from container operators. ‘Other efficiency savings’ (minimum level of new benefits to container operators that make the project viable) are set so that the project economic rate of return (ERR) equals the opportunity cost of capital. Thus, net economic benefits are equal to the externality reductions to road users and the environment. The principal beneficiaries are bus passengers.

b

a

Container operators. Sri Lanka Railway.

Environment PM10 SO2 NOx GHG emissions Total

Time savings Tolls Petrol fuel tax Diesel fuel tax Diesel savings Petrol savings Deadweight losses VOC savings Fees to SLR/ICD Other efficiency savings Capital cost O&M costs

6736

0

44 765

5927 0

Low income (bus)

1042

85 0

1 0

19

927 0 26 4

18 0 1

High income (car)

Road users Med. income (motorcycle)

Table 11.21 Costs and benefits of the PICD

920

0

273

647 0

Freight (truck)

2957 −6579 919

63

2639

COsa

0−75

0 −27 −48

Govt

0

−1712 −4866

6579

SLRb+port

0 0 0 0 8642

10 157 0 0 0 1101 86 0 2957 0 919 −1712 −4866

Total

31

7 11 13

Local

12 12

Global

Environment

7 11 13 12 8685

10 157 0 0 0 1101 86 0 2957 0 919 −1712 −4866

Total


385

Table 11.22 Benefits and costs NPV in Rs million Road users VOC savings Time savings Fuel taxes Fees Environment PM10 NOx SO2 GHG Total

736 512 30 ×

1277

Students

Govt

Total

−30 ×

736 512 0 0

−30

0 0 0 0 1247

× ×

Local env.

Global env.

Total 736 512 0 0

13 25 24 61

33 33

13 25 24 33 1342

Positive value = benefit; negative value = cost; × = undetermined; fuel savings included in VOC savings.

11.4.4 Reintroducing school buses Until the early 1980s, Colombo City had a reasonably well patronized school bus service operated by the state-owned Sri Lanka Transport Board. However, with cutbacks in state-owned bus operations, school bus services have been taken over by private vans that offer a charter service for a monthly fee. In 2001, only 50–60 school buses operated in Colombo, compared with 2167 vans (having increased from 1619 vans in 1996 at 5% per year). There are about 16 students per van. These school vans have worsened congestion. Surveys indicate that about half the students travelling in vans would transfer to a dependable school bus service. A bus could carry 80 students – equivalent to five vans, with a saving of at least 50% in road space. A 1996 survey showed that the average cost of school van service was SL Rs570/month per student, only slightly lower than that charged by office vans (SL Rs650/month). Table 11.22 shows the NPV of benefits and costs of this policy option over 20 years. Environmental benefits are 7% of total economic benefits. The distributional impacts are unclear. How the vehicle operating cost savings would be distributed among bus operators, students and government is difficult to say. Utility gains from time savings to students are another undetermined benefit. Even if new buses were purchased for SL Rs860 million (with zero scrap value for replaced vans), the net benefits would still be SL Rs482 million. Thus the reintroduction of school buses is self-evidently win–win, and is therefore strongly recommended. 11.5 Sustainable transport policy in Sri Lanka 11.5.1 Fuel and vehicle taxes One major policy priority for making transport development more sustainable is the rationalization of fuel and vehicle taxes. A major issue is to reduce the gap between (low) diesel

386


and (high) petrol taxes. Indeed, based on road damage externalities, the pollution tax on diesel should be greater than that on petrol. If fuel taxes are to be equalized on the basis of revenue neutrality, then, from an environmental perspective, there is a slight preference for an equalization based on carbon emissions (giving diesel a slightly higher tax rate than petrol on a Rs/litre basis). The high tax on petrol may not serve the social objective of income redistribution. In fact, a major proportion of petrol taxes falls on the 700 000 motorcycle and three-wheeler owners, while private owners of petrol cars account for under 30% of vehicle-kilometres. The new petroleum pricing system introduced in 2002, which is better aligned to international oil price levels, is more efficient than the previous ad hoc system. However, the relative prices of diesel and petrol remain unsatisfactory, and do not reflect actual road damage and environmental externalities.

11.5.2 Reducing sulphur in auto-diesel As in the case of leaded petrol, the actual sulphur content in diesel has been much lower than the 1.1% of the specification. Nevertheless, the benefits of reducing sulphur in diesel fuel are still high, as evidenced by the differential between international prices of gasoil having varying sulphur content. Given that modifying the kerosene unifiner for hydrotreating of gasoil is now a sunk cost, the refinery now produces large quantities of 0.1% sulphur gasoil, which can be blended with imports to almost any desired specification. There is little doubt that a 0.5% sulphur specification is cost-effective from a social standpoint, using highly conservative values for the health damage of SO2. Using damage values in the ‘Six Cities Study’, even a reduction to 0.3% sulphur would be cost-effective.

11.5.3 LPG conversion of petrol cars Although the growth rate of LPG conversion of petrol vehicles has slowed, 10% of the petrol-engine fleet runs on LPG, of which over 70% involve conversions to bottled gas. This conversion is driven entirely by distortions of fuel taxation policy. Most of them appear to be high-mileage vehicles (mainly taxis), where conversions have been highly profitable (in financial terms). The main environmental benefit of LPG conversion is the avoided lead emissions from leaded petrol, which disappears with the introduction of unleaded petrol. Any remaining environmental benefits are dwarfed by the high economic costs of vehicle conversion and the higher economic costs of imported LPG and filling station costs. This is true even if the new ‘tanktainer’ concept were implemented. There is a major loss of government tax revenue from LPG conversion (given that petrol is more highly taxed). This is effectively a subsidy to taxi fleets (and their high-income passengers) and to businesses, for whom the conversion costs are justified by high mileage. The obvious remedy would be to tax auto-LPG at filling stations at a rate commensurate with petrol, but this is likely to encourage use of bottled gas (unless the tax on bottled gas


387

Table 11.23 Percentage of environmental benefit in total social benefit Option

Percentage

Congestion fee School bus Tax equalization Unleaded petrol Carbon tax (incremental) Carbon tax (equalization) Ban on 2-stroke motorcycles CKE PICD Railway electrification Sulphur 0.5% Sulphur 0.25% LPG (versus leaded petrol) LPG (tanktainer) LPG (versus unleaded petrol)

1 5 30 120 40 31 135 3 0 2 116 130 472 148 0

Where the figure exceeds 100%, it means that the option has a negative NPV before environmental impacts are included. Thus, with a ban on 2-stroke motorcycles, the value of (positive) environmental benefits is 135% of the (negative) non-environmental benefits (i.e. of the non-environmental costs).

was also raised, which will penalize homes). Efforts to ban bottled gas for auto use would also fail. The poor overwhelmingly still use fuelwood for cooking, and bottled gas is largely used by higher-income groups – the same groups who also use motorcycles and cars. Therefore, if a revenue neutral tax reform were undertaken (by equalizing tax on LPG and petrol), the distributional impacts would cancel out, with the remaining main benefit of Sri Lanka avoiding uneconomic use of LPG for transport.

11.5.4 Transportation infrastructure projects Two of the transportation infrastructure projects (the airport expressway and the port inland clearance depot) are win–win, while railway electrification is uneconomic. Meanwhile, Table 11.23 shows that the proportions of environmental benefits of the expressway and the dry container port in the total benefit are quite small (3% and QL, posing major risks to human health. Clearly, the remedy is not to stop growth, but rather to introduce complementary measures that establish appropriate energy prices. First, fuel prices may be increased to more efficient levels by eliminating economic subsidies (ESs) – e.g. to reflect correctly the opportunity cost of time wasted due to road congestion. The resulting efficient price (pec) would reduce the air pollution level to Qec, which still exceeds QL. Second, an additional environmental externality cost (EE) may be charged, to reflect health costs (lung diseases, lead poisoning, etc.), and thereby establish the environmentally adjusted price (pen). The air pollution index now falls to Qen< QL , which is a sustainable fuel price, since the health-determined safety standard QL is no longer exceeded. 14.3 Calculating economically efficient prices based on strict LRMC In this first stage calculation, strict LRMC (and the optimal investment programme) are estimated using shadow prices (instead of market prices), which correct for distortions in the economy.

14.3.1 Estimating strict LRMC Strict LRMC is defined as the incremental cost of optimal adjustments in the system expansion plan and system operations attributable to a small, sustained increment of

476


demand. LRMC must be structured within a disaggregated framework, including differentiation of marginal costs by time of day, voltage level, geographic area, season of the year and so on. The degree of structuring and sophistication of the calculation depends on data constraints and the desired results, given the practical problems of computing and applying a complex tariff; e.g., in theory, the LRMC may be estimated for each individual user at each moment of time. The method of calculating strict LRMC is summarized below (see the detailed theory and case studies in Munasinghe (1990b) and Munasinghe and Warford (1982). Cost categories and rating periods The three broad categories of marginal costs are: (a) capacity costs; (b) energy costs; and (c) consumer costs. Electricity is generated by power plants and fed successively into the extrahigh- and high-voltage (EHV and HV) transmission systems, the medium- and low-voltage (MV and LV) distribution systems, before reaching the end user. Marginal capacity costs include the investment costs of generation, transmission and distribution facilities associated with supplying additional kilowatts. Marginal energy costs are the fuel and operating costs of providing additional kilowatt-hours. Marginal customer costs are the incremental costs directly attributable to users, such as costs of hook-up, metering and billing. Operation and maintenance (O&M) costs, and administrative and general (A&G) costs must also be allocated to these basic cost categories. Finally, these elements must be structured by time of use, etc. The first step in structuring is the selection of appropriate rating periods. System-load duration curves and generation schedules should be examined to determine periods during which demand presses on capacity and supply costs are highest. These critical periods may be due to daily demand variations (e.g. evening lighting load) or seasonal variations in both demand (e.g. summer air conditioning load) and supply (e.g. dry season for hydro systems). We begin with a simple all-thermal system that does not exhibit marked seasonability of demand, choosing only two rating periods by time of day, i.e. peak and off-peak. Seasonal variations in LRMC and the analysis of hydroelectric systems are discussed later.

14.3.2 Marginal capacity costs The typical power system load during 24 hours may be divided into two pricing (or rating) periods: peak and off-peak. As demand rises over time, the peak load also grows. In Figure 14.7, the resulting forecast of peak demand is given by curve D, starting from the initial value MW. The LRMC of capacity is the ratio ΔC/ΔD, where ΔC is the change in system capacity costs associated with a sustained increment ΔD in the long-run peak demand (as shown by the dashed curve in Figure 14.7). The increment of demand ΔD is marginal both in time, and in terms of MW. In theory, ΔD can be either positive or negative, and generally the ratio ΔC/ΔD will vary with the sign as well as the magnitude of ΔD. If many such values of ΔC/ΔD are computed, it is possible to average them to obtain the LRMC.

14 Resource-pricing-policy applications

477 D+ΔD

peak MW

D advanced capacity originally planned capacity

MW0 O

T

time (years)

Figure 14.7. Forecast of peak power demand and incremental demand.

In an optimally planned system, new load would normally be met by advancing future plant or inserting new units, such as gas turbines or peaking hydro; see Figure 14.7. Using a generation planning model, it is easy to determine the change in capacity costs ΔC by simulating the expansion path and system operation, with and without the demand increment ΔD. This process may also be generalized to derive a more complex tariff structure with many rating periods. The method simulates the optimal system planning process, using the dynamic LRMC concept. When constraints due to time, data and resources preclude this ideal approach, more approximate methods may be used. Several practical methods of estimating LRMC are provided in Munasinghe (1979a, 1990b). Simple considerations based on more static interpretation of the LRMC often yield good results. Suppose that gas turbines are used for peaking. Then the LRMC of generating capacity (LRMCGen. Cap.) may be approximated by the cost per kilowatt installed, annuitized over the expected lifetime. This figure must be adjusted for the reserve margin (RM %) and losses due to station use (Lsu %). Thus a typical expression would be: LRMCGen: Cap: ¼ ðannuitized cost kWÞð1 þ RM%Þ=ð1 Lsu %Þ: In our model, all capacity costs are charged to peak-period users. Thus, if capacity costs of base-load generating units are included, it is important to net out potential fuel savings due to displacement of less efficient plant by these base load units (see Appendix A, Section 14.6). It would be incorrect to charge peak consumers the high-capacity costs of base load units (such as nuclear), e.g. encouraging them to install their own captive gas turbine plant. Next we examine transmission and distribution (T&D) investment costs (except customer costs), which are allocated to incremental capacity, because the designs of these facilities are determined principally by the peak kilowatts that they carry rather than the kilowatt-hours. However, particularly at the distribution level, the size of a given feeder may depend on local

478


peak demand, which may not occur within the system peak period, and this could complicate the problem of allocating distribution capacity costs among the various rating periods (Boiteux and Stasi, 1964). Structuring by voltage level is introduced at this stage, in three supply categories: high, medium and low (HV, MV, LV). Since consumers are charged only upstream costs, capacity costs at each voltage level must be identified. The simplest approach is to use the average incremental cost (AIC) method to estimate the LRMC of T&D. Suppose that in year i, ΔMWi and Ii are the increase in demand served (relatively to the previous year) and the investment cost, respectively. Then, the AIC of capacity is given by " # " # T T þL X X AIC ¼ Ii =ð1þrÞi DMWi =ð1þrÞi ; 0

L

where r is the discount rate (e.g. the opportunity cost of capital), T is the planning horizon (e.g. 10 years) and L is the average time delay between the investment and commissioning dates for new facilities. We note that, in the AIC method, the actual additional increments of demand are considered as they occur, rather than the hypothetical fixed demand increment ΔD used (more rigorously) in calculating generation LRMC. However, because there is no problem of plant mix with T&D investments, AIC and the hypothetical increment method will yield similar results, while AIC is also usually much easier to calculate using readily available planning data. Furthermore, AIC is the unit cost which equates the present discounted value of power output (denominator) and its supply costs (numerator). Thus, it is the monetary value of ΔMWi that is effectively discounted, rather than the physical units. An alternative method of determining marginal T&D costs at various voltage levels is to use historical data to fit regression equations such as ðtransmission costsÞ ¼ a þ bðpeak demandÞ: However, there is no guarantee that such a past relationship would hold true in the future as the system expands. Let ΔLRMCHV be the AIC of EHV and HV transmission, annuitized over the life of the plant (e.g. 30 years) to yield marginal costs. Then, the total LRMC of capacity during the peak period, at the HV level, would be given by LRMCHV Cap: ¼ LRMCGen:Cap: =ð1 LHV %Þ þ DLRMCHV ; where LHV % is the percentage of incoming peak power that is lost in the EHV and HV network. This procedure may be repeated at the MV and LV levels. The LRMC of T&D calculated in this way is based on actual growth of future demand, and averaged over many consumers. However, facilities associated with given generating sites or loads should be specifically allocated to those uses rather than averaged out, e.g. transmission spur line, or distribution line to a given customer.


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14.3.3 Marginal energy costs and treatment of losses The system lambda concept is useful to calculate marginal energy costs. The LRMC of peak-period energy will be the running costs of machines used last in the merit order, to supply the incremental peak kilowatt-hour (ΔD). In our model, this would be the fuel and operating costs of gas turbines, adjusted by relevant peak loss factors at each voltage level. Similarly, the LRMC of off-peak energy would be the running costs of least-efficient baseload or cycling plants used during this period. Exceptions occur when the marginal plant used during the rating period was not necessarily the least-efficient machine that could have been used. For example, less-efficient plants which have long start-up times, and are required in the next rating period, may be operated earlier in the loading order than more efficient plant. This would correspond to minimization of operating costs over several rating periods rather than on an hourly basis. Again, since the heat rate of the plants could vary with output level, the simple linear relationship usually assumed between generation costs and kilowatt-hours may need to be replaced by a more realistic non-linear model. Loss factors for adjusting off-peak costs will be smaller than those for the peak period when current flows are greatest (Munasinghe, 1979a). The treatment of losses raises several important issues. While total normal technical losses vary from system to system, if these are much greater than about 15% of gross generation, then loss reduction should have a high priority. When engineering losses in excess of acceptable levels are routinely passed onto the customer, it acts as a disincentive to efficiency improvements. Losses due to theft and unpaid bills are also often loaded onto paying customers. Here again, the issue is whether these non-technical losses could be reduced by appropriate measures, or if incremental consumption always has an avoidable component of such losses associated with it. Theft in US systems is about 2% of gross generation, but norms in developing countries may have to be set higher (Munasinghe and Warford, 1982). LRMC analysis at generation, transmission and distribution levels helps establish whether marginal costs are large because of overinvestment, high losses, or both. 14.3.4 Consumer costs It is difficult to allocate part of the distribution system investment costs to customer costs, on the basis of a skeleton system required to serve a hypothetical minimum load. Similarly, attempts have been made to fit past data with equations such as ðdistribution costsÞ ¼ a þ b ðpeak demandÞ þ c ðnumber of customersÞ: Such regression analyses are also problematic because peak demand and number of customers are usually highly correlated. Therefore, general distribution network costs may be considered as capacity costs, while customer costs are defined as those which can be readily allocated to users. Initial customer costs include items such as service drop lines, meters and labour for installation. They may be charged to the user as a lump sum or distributed payments over time.

480


Recurrent customer costs that occur due to meter reading, billing, administrative and other expenses, could be imposed as a monthly flat charge, in addition to kilowatt and kilowatt-hour charges. Allocation of incremental (non-fuel operation, maintenance and administrative costs among the categories of capacity, energy and customer costs, varies from system to system, but these costs are usually small.

14.3.5 Analysis of hydroelectric generation Several specific issues arise in the analysis of hydro systems, when seasonal variations in LRMC are important (Munasinghe 1990b; Turvey and Anderson, 1977). In an all-hydro system, the LRMC of generating capacity would be based on the cost of increasing peaking capability (i.e. additional turbines, penstocks, expansion of powerhouse, etc.), while incremental energy costs would be the costs of expanding reservoir storage. When there is spilling of water (e.g. wet season), incremental energy costs would be small (e.g. O&M costs only), and when demand does not press on capacity, incremental capacity costs may be ignored. However, if the system is likely to be energy-constrained, and all-incremental capacity is needed primarily to generate more energy because the energy shortage consistently precedes the capacity constraint, then the distinction between peak and off-peak costs, and between capacity and energy costs, tends to blur. In an extreme case, because hydroenergy consumed during any period (except when spilling) leads to a drawdown of the reservoir, it may be sufficient only to levy a simple kilowatt-hour charge at all times, e.g. by applying the AIC method to total system costs. In a mixed hydrothermal system, a general guideline is that if hydro displaces thermal plant during a rating period, then the running cost of the latter is the relevant incremental energy cost. If pumped storage is used, the marginal energy costs or value of water used would be the cost of pumping net of losses. Also, if the pattern of operation is likely to change rapidly in the future (e.g. shift from gas turbines to peaking hydro as the marginal peaking plant, or vice versa), then the value of the LRMC would have to be calculated as a weighted average, with the weights depending on the share of future generation by the different types of plant used.

14.4 Adjusting efficient prices to meet other objectives 14.4.1 Deviations from strict LRMC The strict LRMC calculation completes the first stage of tariff setting. In the second stage, a practical sustainable pricing structure that meets economic second-best, sociopolitical, financial, environmental and other constraints must be derived by modifying the strict LRMC. This adjustment process will result in deviations in both the magnitude and structure of strict LRMC. The tariff structure at this stage may be differentiated by the type of user or by income level. Practical considerations, such as the difficulties of metering and billing, will also affect the final tariff.


481

Constraints that cause the final tariffs to deviate from strict LRMC fall into two categories (Munasinghe and Warford, 1978). The first group of constraints include second-best considerations and subsidized (or lifeline) tariffs for low-income consumers, which may be analysed within an economic framework. The second group consists of all other issues, such as financial viability, sociopolitical constraints and environmental impacts, which cannot be monetized, as well as problems of metering and billing, where strict economic analysis is difficult to apply. These two groups of constraints may be linked, e.g. subsidized tariffs can have simultaneous economic welfare, financial and sociopolitical implications. Second-best considerations A ‘second-best’ departure from strict marginal cost pricing may be needed when prices elsewhere in the economy do not reflect marginal costs (especially for electricity substitutes and compliments). More generally, price distortions affecting inputs into the production of electric power and outputs of other sectors which are electricity intensive (e.g. aluminium) should also be considered. The former type of distortion may be dealt with by direct shadow pricing of inputs, as discussed earlier, but the latter case requires more detailed analysis of the market for the output. As an example of price distortion for an energy substitute, consider the subsidies for imported generators and/or diesel fuel, which exist in some countries. This may encourage private users to set up their own captive plant, even though it is not the least-cost way of meeting the demand (for the whole economy). The best solution may be for the government to revoke such subsidies or restrict imports of private generating plant. However, if transportation policy dictates the need to maintain subsidies for diesel fuel, or if strong pressure groups make such changes politically unfeasible, the low cost of (subsidized) private generation may require the setting of an optimal grid-supplied electricity price which is below strict LRMC. The extent of the deviation from strict LRMC is determined by the magnitude of the subsidy and substitutability of the alternative energy source (Munasinghe and Warford, 1982). A related question concerns the availability of subsidized kerosene, which is aimed mainly at providing basic energy needs for low-income consumers at prices they can afford. The subsidy may also prevent low-income users (especially in developing countries) from shifting to use of non-commercial fuels for heat, e.g. wood, the overuse of which leads to deforestation and environmental harm. If we assume the kerosene subsidy as given, then the price of electricity must be reduced (to compete for lighting). Meanwhile, undesirable leakages may occur if cheap kerosene is not targeted to the poor, e.g. it is often mixed with more expensive petrol or diesel and used by wealthy car owners or industrialists. 14.4.2 Social considerations − subsidized prices and lifeline rates In addition to the second-best economic arguments, sociopolitical or equity arguments are made in favour of ‘lifeline’ rates to meet basic energy needs, especially where costs of electricity use are high relative to income. The ability of power suppliers to act as discriminating monopolists permits systematic practical adjustments to make energy prices more sustainable, within the analytical framework described in the following.

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Sub-national and system applications unit price, p G I2 > I1 H

pe A

pS

O

I1 F

B

Q1

Qmin

Q2

quantity

Figure 14.8. Basis for the social or lifeline tariff.

The subsidized ‘social’ block, or ‘lifeline’ rate, for low-income consumers has an important socioeconomic rationale, based on the equity argument. We clarify this point with the aid of Figure 14.8, which shows that respective demand curves AB and GH for low(I1) and average- (I2) income domestic users, the social tariff pS over the minimum consumption block O to Qmin and the marginal cost-based price level pe. If the actual tariff p = pe, then the average household will be consuming at the ‘optimal’ level Q2, but the poor household will not be able to afford the service. If increased benefits accruing to the poor have a high social weight or value, the consumer surplus portion ABF should be multiplied by the appropriate social weight (greater than unity) – see Appendix A, Section 14.6. Then, although point A lies below pe (in market prices), the weighted distance OA may be more than the marginal supply cost. The increasing block tariff shown in Figure 14.8, consisting of the lifeline rate pS, followed by the full tariff pe, helps to capture this ‘weighted’ consumer surplus of the poor user. It does not affect the optimum consumption pattern of the average consumer, if we ignore the income effect due to reduced expenditure of the average consumer for the first block of consumption, i.e. up to Qmin. In practice, the magnitude Qmin should be based on acceptable criteria for identifying ‘low-income’ groups, and reasonable estimates of their minimum consumption levels (e.g. sufficient to supply basic requirements for lighting, heating, appliances). In rich countries, where the average home uses around 1000 kWh/month, the minimum consumption level may be several hundred kWh/month, while in developing countries, where average electricity use is much lower, Qmin is typically around 50 kWh/month. For pS, a simple model yields pS ¼ strict LRMC ðpoor person0 s income=critical incomeÞ; where the critical income describes a nationally established poverty line (Munasinghe and Warford, 1978). The utility revenue constraints and the ability to pay of the poor consumer would also be considered in determining pS and Qmin. This approach may be reinforced by


483

an appropriate connections policy (e.g. subsidized house connections). The rights of poor and disadvantaged customers may also be protected through legislation, to protect against unfair termination of service.

14.4.3 Financial viability The most common financial constraints relate to revenue requirements of the sector, and are embodied in criteria such as some target financial rate of return on assets, or an acceptable rate of contribution toward the future investment programme. In principle, for state-owned power utilities, the most efficient solution would be to set price equal to marginal cost and rely on government subsidies (or taxes) to meet the utility financial needs. In practice, some measure of financial autonomy and self-sufficiency is an important goal for the sector. Because of the premium that is placed on public funds, a pricing policy that fails to achieve minimum financial targets for continued operation of the power sector would rarely be acceptable. However, marginal cost pricing more typically results in financial surpluses well in excess of traditional revenue targets, which may lead to consumer resistance. Therefore, revenue changes have to be achieved by adjusting strict marginal-cost-based tariffs. A widely used criterion of financial viability is an acceptable rate of return on assets – net operating income after taxes given as a fraction of net fixed assets in operation plus adequate working capital (in some cases). In the case of US private utilities, regulatory authorities have traditionally imposed a fair rate of return as an upper limit on earnings and, therefore, on average price per unit sold (Garfield and Lovejoy, 1964). Where utilities are government owned, as in many developing countries, the target rate of return is usually considered a minimum requirement to help resist sociopolitical pressures that tend to keep prices low. If the asset base is defined in revalued terms, then this requirement is more consistent with the forward looking approach of the LRMC. Another future-oriented financial criterion, useful for a rapidly expanding system, requires the utility to make a reasonable contribution to its future investment programme from its own revenues. This self-financing ratio is often expressed by the amount of internally generated funds available after operating costs and debt service, as a fraction of capital expenditures. The application of the financial criteria may raise serious conceptual and practical problems. Thus, if a rate of return test is to be used, then the question of asset revaluation arises. The use of historical costs for working assets, typically original cost less depreciation, would tend to understate their value when capacity costs are rising rapidly. If assets are to be revalued, the costs of either (a) exactly reproducing the power system at today prices or (b) replacing it with an equivalent system at today prices might be used after netting out depreciation to allow for the loss of value due to obsolescence of existing equipment. Difficulties of interpretation will occur in the practical application of either approach. Whichever combination of criteria are used, it is important to include the initial tariffs based on strict LRMC in the utility financial forecast. Then, these first-round tariffs may be adjusted through an iterative process until the chosen parameters of financial viability fall within the acceptable range. Although this process is usually quite ad hoc, some practical

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guidelines may be effectively used for reconciling strict LRMC and the revenue requirement. The relative adjustments to strict LRMC between major consumer categories (such as residential and industrial), as well as among the different rating periods (such as peak and off-peak) within a given consumer category, will determine the share of the revenue burden to be borne by each user group in a given rating period. A simple and equitable method of adjustment is to retain the relative structure of LRMC and vary the average rate level by equiproportional changes. In general, this procedure will not be economically efficient. The ‘inverse elasticity’ pricing formula allocates the price burden among various consumer categories, so that greater divergence from the marginal opportunity-cost-based price occurs for consumer groups with the lowest price elasticity of demand, and vice versa. This will result in the smallest deviation from ‘optimal’ levels of use derived from strictly efficient prices (Baumol and Bradford, 1970). A simple version is given by ð1 LRMC1 =p1 Þ=ð1 LRMC2 =p2 Þ ¼ ð1=e1 þ 1=e12 Þ=ð1=e2 þ 1=e21 Þ; where LRMCi and pi are the respective strict LRMC and price of good i; while ei = (∂Qi/∂pi)/ (Qi/pi) and eij= (∂Qi/∂pj)/(Qi/pj) are the own- and cross-price elasticities of demand (Q) with respect to price (p). The two goods 1 and 2 may be interpreted as either the electricity consumption of two different consumer groups in the same rating period or the consumption of the same consumer groups in two distinct rating periods. In practice, a larger number of consumer types and rating periods must be considered, and application of the rule will be limited by lack of data on price elasticities. This technique may appear to penalize some customers more than others, thus violating the fairness objective. Adjustments involving lump-sum payments and rebates or changes in user and connection charges are also consistent with economic efficiency, if electricity usage is relatively unaffected by these procedures, i.e. use depends mainly on the variable charges. Another related approach that reduces revenues is to charge strict LRMC only for marginal use and reduce the price for initial consumption blocks. Such subsidies on customer charges, or on the initial block, also meet lifeline-rate needs for poor consumers, but tend to complicate the price structure. In practice, an eclectic approach involving a combination of all these methods is most likely to be successful.

14.4.4 Environmental and other considerations Energy conservation is an environment-related goal that is also used to deviate from strictly efficient prices, but it may run counter to subsidy arguments. One solution is to encourage energy efficiency in productive sectors (via higher prices) and target energy subsidies to meet the basic needs of the poor. In other cases, conservation and subsidized energy prices are consistent. For example, cheap kerosene in rural areas might reduce high fuelwood consumption and prevent deforestation and erosion.


485

The decision to electrify a remote rural area, which may also entail subsidized tariffs to poor homes, could be made on completely non-economic grounds, e.g. to maintain a viable regional industrial or agricultural base, stemming rural to urban migration, or alleviating local political discontent. However, the indirect economic benefits of such a policy may be greater that the direct efficiency costs of diverging from strict LRMC – especially in the developing world, where energy is costly relative to incomes and the administrative or fiscal machinery to redistribute incomes or achieve other development goals is ineffective. In practice, price increases need to be gradual, in view of the costs which may be imposed on those who have already incurred expenditures on electrical equipment and made other decisions, while expecting little or no changes in traditional power-pricing policies. The efficiency costs of ‘gradualism’ can be seen as an implicit shadow value placed upon the social benefits that result from this policy. Another macroeconomic-type argument that power-price increases may be inflationary is rarely valid, since costs of electricity use are usually a small fraction of home expenses and of industrial production costs. Low electricity prices cause more serious issues by overstimulating demand and limiting supply investments. Metering, billing and customer comprehension Tariff structures must be simplified, due to practical problems and costs of metering and billing, and to make it comprehensible to users – who are expected to adjust their consumption according to the price signal. Thus, user classes, rating periods, voltage levels, etc, need to be limited. Metering sophistication depends on the practical problems of installation and maintenance and on the net benefit of metering based on a CBA that compares the lower supply costs of reduced use with the cost of metering plus the decrease in net consumption benefits. Thus for very poor consumers paying a subsidized rate, a simple current-limiting device may suffice, because the cost of even simple kilowatt-hour metering may exceed its net benefit. In general, various forms of peak-load pricing (i.e. maximum demand or timeof-day metering) would be more applicable to large MV and HV industrial and commercial consumers (Munasinghe, 1990b). Most LV consumption, especially for households, is metered only on a kilowatt-hour basis, with the price per kilowatt-hour based on a combined energy and ‘rolled in’ capacity charge (e.g. using coincidence and load factors). More sophisticated meters (such as time-of-day meters with synchronous clocks) may be affected by power outages. At the other end of the scale, current-limiting devices are easier to tamper with. The concept of homeostatic utility control is growing, using advanced solid-state technology (including use of microprocessors) to implement sophisticated metering, automatic meter reading, load management techniques and pricing structures (MIT, 1979). In contrast, some developing countries may lack technically skilled labour for installation and maintenance of sophisticated meters, or even reliable meter readers. Therefore, choice of appropriate metering is usually very country-specific, and is likely to involve many practical considerations.

486


Gas offers the potential to apply quite sophisticated pricing approaches, including different charges for various consumption blocks with conventional metering. However, for liquid fuels like kerosene, subsidized or discriminatory pricing would usually require schemes involving rationing and coupons, and could lead to leakage and abuses.

14.5 Sustainable pricing of water resources The integrated framework for sustainable energy pricing set out above may be adapted mutatis mutandis to price water resources (Munasinghe, 1992b). Water supply systems (for irrigation, potable water, etc.) may be analysed in the same way as electric power systems. Below, we explain aspects of SPP specific to water resources; see also Chapter 12.

14.5.1 Joint-cost allocation A typical multipurpose reservoir could yield benefits in terms of potable water, irrigation, hydropower, navigation, flood control, fishing, etc. While total project costs are most useful for the overall investment decision, the exact allocation of such joint costs are important for cost recovery and efficient pricing of water to various uses (Munasinghe, 1992b). Thus, if a dam provides urban water supply, the share of costs allocated to potable water will determine the price of water to consumers. There is no theoretically rigorous method of allocating joint costs, to meet various requirements such as economic efficiency, social equity, etc. One approach may be to simulate how incremental project costs might vary for a small change in one output (e.g. providing more potable water by raising the dam height). However, this method may also change the outputs and benefits of other project goals (e.g. flood control). The allocation of such truly joint costs gives rise to major problems. A more equitable method is the allocation of total costs to different uses in proportion to the benefits accruing to those uses. However, this approach is difficult to apply, especially when the benefit measurement is not consistent or accurate across different outputs and uses. A related and more practical method is the separable costs and remaining benefits (SCRB) technique, which offers a good compromise between economic efficiency, social equity and ease of application – in the spirit of the sustainomics approach and sustainable resource pricing. This method is shown in Table 14.1 for the simple case of a dam with two typical purposes (hydropower and drinking water). The procedure can be generalized easily to cases involving more outputs or purposes. The first step identifies a set of single-purpose alternative schemes that will provide the same benefits as the multipurpose project. In our example, the two alternatives might be an equivalent thermal power plant and the pumping of the same volume of water from an underground aquifer, with cost adjustments for transport of the electricity and water, to the point of delivery. The costs of the singlepurpose alternatives (2) are compared with the benefits corresponding to each purpose (3), and the smaller of these quantities (4) is selected. The procedure eliminates the risk of


487

Table 14.1 Separable costs and remaining benefits (SCRB) technique for joint-cost allocation: a simple two-purpose example Project purpose Item (1) Total multipurpose project costs (2) Alternative single-purpose project cost (3) Benefits of multipurpose projects (4) Smaller of item (2) or (3) (5) Separable costs (6) Remaining benefits (item (4) – item (5)) (7) Remaining benefits fraction (8) Residual joint cost (item (1) – item (5)) (9) Allocation of residual joint cost (10) Total allocated cost (item (5) + item (9))

Potable water

Hydropower

a c c e g = (c − e) [g/(g + h)]

b d b f h = (b − f ) [h/(g + h)]

Total i

gk/(g + h) e + [gk/(g + h)]

(e + f ) (g + h) 1.0 k = [i − (e + f )] hk/(g + h) [i − (e + f )] f + [hk/(g + h)] i

having to rely on unrealistic and expensive alternative projects. Item (5) shows the separable costs, defined as those directly attributable to a specific purpose (e.g. transmission pipes that carry the potable water away from the dam), plus the portion of the joint costs (e.g. the dam) that is traceable to the inclusion of a specific purpose within the project. The remaining benefits (6) are defined as the difference between items (4) and (5). The residual joint costs (8) are the difference between the total project costs (1) and the separable costs (5). These residual joint costs are allocated to the different purposes (9) in direct proportion to the remaining benefits fraction (7). Finally, the sum of separable and allocated joint costs yields the total allocated costs (10). The above process is unlikely to provide a rigorous apportionment of project costs. However, such allocated costs are usually only a small fraction of total costs of a given water supply system. Thus, inaccuracies in the joint-cost allocation exercise will not significantly affect the overall economic and financial analysis of the water system.

14.5.2 Environmental impacts Environmental changes due to water-related activities can have considerable economic and social impacts (see Chapter 12). These effects need to be included in the long-term calculation of costs to give a realistic estimate of the true costs of supplying water. Those responsible for negative externalities should bear the burden of the costs passed on to others (see Chapter 3). Prices based on the LRMC provide a vehicle for implementing this concept. For example, if a new storage dam results in the flooding of land having ecological, recreational or agricultural value, then these costs should be reflected in the LRMC. Similarly, if water is extracted from an underground aquifer, externality costs might include damages to buildings or infrastructure due to land subsidence, depletion costs and groundwater pollution, which impose further costs on future users of water, e.g. due to saline water intrusion (see Section 12.4).

488


While some pollution and depletion costs may be difficult to quantify, they are already being passed on to consumers in many countries. Environmental costs are also included in the mitigation or preventive aspects of water-resource projects, and may constitute 5% of investment costs. Section 12.4 sets out a case study involving groundwater depletion. 14.5.3 Marginal costs of water supply and prices Based on the framework of Sections 14.1 to 14.3, the total cost of using a water resource is the sum of three components: (1) the conventional cost of extraction, treatment, storage, bulk transmission, distribution and disposal; (2) the depletion cost due to higher expenses borne by future users of the same source; and (3) the additional cost due to environmental harm, or cost of mitigating such impacts. There may be overlap among these categories, depending on their interpretation. Next, we estimate the LRMC of water using the AIC method (see Section 14.3). In a water system, water is produced at the headworks, and then conveyed to users via pipelines or channels. For example, in the case of piped water systems, water is transported through trunk mains, to primary and secondary distribution systems, and finally to the consumer. First, without differentiating between peak and off-peak periods, we define the AIC (i.e. the LRMC) of water produced at the headworks as follows: T X ðIHt þ RHt Þ=ð1 þ rÞt AICHP ¼

t¼0

T þL X

; QHt =ð1 þ rÞ

t

t¼L

where, IHt , RHt and QHt are the respective investment, incremental operating and maintenance (O&M) cost and incremental water produced at the headworks in year t and r is the discount rate (e.g. opportunity cost of capital). AIC is the unit cost, which equates the present discounted value of water output to supply costs, and it is the monetary value of Q that is effectively discounted rather than the physical quantity. The AIC of water delivered from the headworks to the trunk mains is given by AICHS ¼

AICHP ; 1 LFH

where LFH = LH/Q1 is the fraction of water lost at the headworks. The AIC of the trunk main system is given by T X

AICM ¼

t¼0

ðIMt þ RMt Þ=ð1 þ rÞt TþL X t¼L

; t

QMt =ð1 þ rÞ


489

Table 14.2 Average incremental costs of existing and future water-supply projects for some developing countries; 1988 prices Country: city

Present project

AIC (US $/m3)

Future project

AIC (US $/m3)

Algeria: Algiers Bangladesh: Dhaka China: Shenyang China: Yingkuo India: Hyderabad India: Bangalore Jordan: Amman Mexico: Mexico City Peru: Lima

groundwater groundwater groundwater groundwater reservoir (phase 2) pumped (river) groundwater groundwater surface

0.23 0.08 0.04 0.07 0.17 0.1 0.41 0.54 0.25

surface water (raw) surface water surface water reservoir intakes reservoir (phase 3) pumped (river) surface – piped pumped (river) interbasin transfer

0.5 0.3 0.11 0.3 0.62 0.22 1.33 0.82 0.54

Source: Munasinghe (1992b).

where IMt and RMt are the respective investment and incremental operating and maintenance (O&M) costs in the trunk mains system and QMt is the incremental water flowing through the trunk mains system in year t. Finally, the AIC of water delivered out of the trunk main system is given by AICMS ¼

AICHS þ AICM ; 1 LFM

where LFM = LM/Q1 is the fraction of water lost in the trunk main system. Corresponding expressions may be derived for the AIC of water delivery at all successive levels – i.e. primary and secondary distribution. Accurate estimation of the AIC for water is important for decision making, because the costs of supplying water are rising, while prices have failed to keep up. Between 1966 and 1981, the AIC of water (at 1988 prices) per cubic metre of water was US $0.49, whereas the average water tariff was US $0.26. Since unaccounted for water (or losses) are around 35% for all the projects, the effective price per cubic metre produced was US $0.17 or only onethird of the AIC. During the period 1987–1990, the AIC was US $0.55 (1988 prices), while the average price was US $0.32 per cubic metre, not including unaccounted for water (Munasinghe, 1992b). The AIC is not only greater than tariffs, but also rising due to more difficult water supply conditions in many developing countries (Table 14.2). Often, the AIC of urban water supplies are commonly two to three times greater than the cost of existing water-supply schemes (Munasinghe, 1992b).

14.5.4 Sewerage charges and pollution externalities Wastewater costs are generated by higher levels of water supplied to growing populations. Such costs vary widely, and are borne by consumers themselves or by the wider community

490


or public authority. They must be included in the water tariff or charged separately – e.g. a sewer fee based on water use. Costs may be incurred for sanitation and treatment facilities, or as environmental costs due to wastewater impacts, such as drinking-water pollution, reservoir eutrophication, loss of work though illness, or reduced property values. Generally, as service levels increase, unit costs of handling wastewater decrease – as long as environmental impacts are limited to their community of origin. However, as environmental impacts of higher service levels extend beyond community boundaries (due to sewerage outflow), unit costs of collection and treatment may rise exponentially with water use. The foregoing underlines the importance of integrating the incremental costs of sanitation into pricing policy. Effective sanitation is always more costly than the water supply from which it is generated. At a low service level (20 litres per capita per day (lcd) – handpump and pitlatrine), the ratio is around 1.3 to 1 and is often absorbed by the users as a self-help input or through cost-recovery. As the service level rises to 700 lcd, this ratio becomes 15 to 1. To prevent environmental externalities, the cost of sanitation services should be factored into water-supply tariffs. The AIC of dealing with wastewater can be calculated based on the cost of conducting sewerage from the consumer, through the collection system to the treatment plant, and back into water courses. The basic AIC at each level of the sewerage system must be adjusted, because leakages of outside effluents into the sewerage collection network actually increases the flow volume. The AIC of sewerage and water supply are added to obtain a combined charge. Two issues arise. First, for the combined water and sewerage charge, it is conceptually difficult to separate the benefit derived by users from each service, or to measure their willingness-to-pay for water and sewerage separately, since they do not usually consider them to be two distinct decisions. This issue is more important for investment analysis than for pricing policy. Consumers use water to the point where benefits per marginal unit of water used equal costs of supply and disposal. Second, the external aesthetic and health benefits enjoyed by the community at large, due to sewerage services, are obvious. There are also indirect external health benefits to the community due to water supply. While users should pay the marginal cost of sewerage disposal wherever possible, there is therefore an economic case for offering a sewerage subsidy to poor consumers who cannot afford to pay for such services. Further, the ‘polluter pays’ principle requires that costs arising from pollution of surface or groundwater resources by wastewater or sewerage sludge should be included in the sewerage charges (see Section 12.4).

14.6 Appendix A: Optimal energy pricing 14.6.1 Socially optimal prices We derive a general expression for the socially optimal price of a given energy type A (based on shadow prices) and apply it to three cases: (a) perfectly competitive economy (classic result); (b) efficient prices, including economic second-best and environmental considerations; and (c) social subsidized prices or lifeline rates for poor consumers.


491

unit price, p

P

E

F G

p – dp

L S (MC)

B p*c MC

A

J

K

I O

Q

H Q + dQ

D Qc

quantity

Figure 14.9. Supply and demand in energy sub-sector A.

Figure 14.9 shows the supply and demand for energy type A, where S is the supply curve or marginal cost of supply (MC) in domestic market prices and D is the demand curve for a specific user. We define ap as the energy conversion factor (ACF), which transforms MC into the corresponding real economic resource cost; i.e. with correct shadow pricing, the marginal opportunity cost is MOC = (ap · MC). Next, we assign a social weight Wc to each marginal unit of use (valued in market prices) for a given individual. Typically, the poorer the user, the higher will be the social weight, to reflect social emphasis on poverty alleviation. Third, if the individual’s consumption of goods and services other than energy type A (valued in market prices) rises by one unit, then the shadow-priced marginal cost of economic resources used (or shadow cost) is given by bc. Starting from the initial price and consumption (p, Q), consider the welfare impact of a small price reduction (dp) and the resultant increase in demand (dQ). Consumer spending on energy falls by (p dQ) (i.e. area IFGH), but income rises by the amount pQ − (p − dp) · (Q + dQ). If none of the latter is saved, this person’s consumption of other goods and services will increase by (Q dp − p dQ), also valued in market prices (i.e. area BEFG minus area IFGH). Therefore, total consumption (energy A plus other goods) will increase by the net amount (Q dp) in market prices. This is the increase in consumer surplus, whose shadow value is Wc(Q dp). Next, consider the resource cost of these changes. The shadow cost of increasing the supply of energy type is given by (ap · MC dQ), i.e. ap times area IJKH, while the resources used up to provide all other goods consumed is bc(Q dp − p dQ). Finally, we ignore the income change of the energy producer by assuming that it is the government. The total increase in net social benefit of the energy price change is given by dðNBÞ ¼ Wc ðp dQÞ ap ðMC dQÞ þ ðWc bc ÞðQ dp p dQÞ: Thus, dðNBÞ=dp ¼ Q½ðWc bc Þ þ nbc nap ðMC=pÞ;where n = (p dQ)/(Q dp) is the elasticity of demand (magnitude).

492


The first-order condition for maximizing the net social benefits is given by d(NB)/dp = 0. This yields the optimal price level: p ¼ ap MC=½bc þ ðWc bc Þ=n:

(14:1)

Case 1 Perfect competition; market prices and shadow prices are equal; income transfer effects are ignored (no social weighting). In this case, ap = Wc = bc = 1, and equation (14.1) reduces to: p* = MC. This is the basic marginal cost pricing result. Net benefits are maximum, with price equal to marginal cost at the market clearing point (pc, Qc). Case 2 Income transfer effects ignored because the marginal social benefit is equal to the marginal cost of consumption. In this case, Wc = bc, and equation (14.1) becomes pe ¼ ðap MCÞ=bc ¼ MOC=bc :

(14:2)

The optimal price p*e ensures efficient allocation of resources, but neglects income distributional considerations. The MOC may be evaluated directly (e.g. border price for a tradable fuel or, for a non-tradable like electricity, by applying shadow prices to the least cost mix of inputs used in production). However, the parameter bc depends crucially on the user. For average consumers, bc is the consumption conversion factor (CCF), based on the resource cost or shadow value of one (market-priced) unit of the household marginal consumption basket. If CCF < 1, then p*e > MOC. If user consumption patterns are not known, bc could be defined broadly as the standard conversion factor (SCF) – for all energy users. Equation (14.2) may be used to correct the economic second-best consideration arising from energy substitution possibilities. Suppose all expenses now spent on energy type A are used to purchase alternative energy type B, which is subsidized (e.g. electricity replaced by kerosene for lighting). In this case, bc is the ratio of the MOC of energy type B to its market price, bc = MOCae/ pae. Thus, p*e = MOC(pae/MOCae). Since the alternative energy B is priced below its border marginal cost (bc > 1), p*e < MOC also. Therefore, the subsidy on substitute energy B prices will yield an optimal price for energy A that is below its shadow cost. Case 3: General subsidized price Equation (14.1) is the optimal energy A price including equity concerns. Consider a group of very poor consumers for whom we may assume that Wc ≫ bc(n – 1). Then, equation (14.1) may be written as ps ≈ n · MOC/Wc. We may simplify further by assuming that n = 1. Thus, ps = MOC/Wc. Suppose that the net income or consumption of these poor consumers (c) is one-third the critical income or consumption level (c) – e.g. a poverty line. Then a simple expression for the social weight is Wc = c /c = 3. Therefore, ps = MOC/3, which is the ‘lifeline’ rate, or subsidized tariff, appropriate to this group of low-income consumers.


493

14.6.2 Dynamic version of marginal cost pricing rule We show that setting price equal to marginal cost over a period of time will maximize the net social benefits of energy use (Munasinghe, 1981). The model also yields the peak/off-peak two-part pricing structure. We seek a set of price (and output) levels over a given period of time that will maximize the present value of net benefits or welfare given by the area under the demand curve minus the area under the supply curve. The net benefits of consumption at any given time t are represented by the following expression: ðQ NB ¼ pðq; tÞdq cðq; KtÞ iðtÞ; 0

where p is consumer willingness-to-pay or the price curve, q is the energy output per unit time, c is the energy production cost function, K is capital stock or available capacity and i is the investment rate. The welfare maximum is derived from the optimal control problem: ZT Max

NB expðrtÞdt 0

subject to KðtÞ qðtÞ 0;

IðtÞ iðtÞ 0;

iðtÞ ¼ KðtÞ þ dKðtÞ;

where r is the discount rate, I is the upper limit on investment rate, δ is the rate of capital depreciation and T is the time horizon. We define the Hamiltonian: H ¼ NB þ lði dKÞ and the corresponding Lagrangian function L ¼ H þ m1 ðK qÞ þ m2 q þ m3 ðI iÞ þ m4 i: By Pontryagin’s maximum principle, the solution to the optimal control problem must also maximize the Lagrangian function at each instant of time over the time horizon under consideration, thus giving rise to the following set of conditions (Takayama, 1985): ð@L=@qÞ ¼ 0; ð@L=@iÞ ¼ 0;

ð@l=@tÞ ¼ r ð@L=@KÞ:

The first condition yields the optimal price: p ðtÞ ¼ ð@c=@qÞ m1 þ m2 : We may interpret the above using the following complementary conditions: m1 ðK qÞ ¼ 0;

m2 q ¼ 0;

m1 0; m2 0:

494


Case 1: Peak period, capacity constrained, K(t) = q(t) > 0. In this case, m2 = 0 and p*1 = (∂c/∂q) + m1. During the peak period, the optimal price is the marginal operating cost ∂c/∂q (with capacity fixed) plus the marginal cost of new capacity (m1). Case 2: Off-peak period, no capacity constraint, K(t) > q(t) > 0 In this case, m1= m2= 0 and p*2 = (∂c/∂q) – only the MOCs enter into the optimal price. These basic marginal cost pricing conditions hold for a dynamic price path over a given time period, just like in the static case (see Section 14.1.3).

14.6.3 Allocating capacity and energy cost to peak and off-peak users We show how an LRMC analysis based on the optimal system expansion plan yields the following idealized conclusions: (1) peak users should pay the peak LRMC of capacity as well as energy; (2) off-peak users should pay only the off-peak LRMC of energy; and (3) LRMC of peak capacity = LRMC of base load capacity − net fuel savings due to this baseload plant.

Figure 14.10 shows the annual LDC for an all-thermal generation system with only two types of plant, whose linearized cost characteristics are given in the Table 14.3. A more realistic generalized system model would have to consider a number of complicating factors, such as a larger number of rating periods and plant types, non-coincidence of the rating installed capacity (kW)

Y –1

N

G

Y

X –1

A

B

K

I

L

C

J

X

E

F O

8760

H peak

off-peak hours per year

Figure 14.10. Plant costs and annual load duration curve (LDC).


495

Table 14.3 Types of generation plant and costs Capacity cost per kW installed (annuitized) Operating costs per hour

Plant type (1) Peaking (e.g. gas turbines, GTs) (2) Baseload (e.g. steam)

a

e

b

f

periods with the economic crossover points between different plant types, economies of scale and variable heat rates for various plants, hydroelectric plant, losses, reserve margins, stochasticity of supply and demand, etc. The key difference in this general case is that a small fraction of capacity costs could be allocated to consumers outside the peak period. As per Table 14.3, the total costs of 1 kW used over h hours per year are given by (1) a + eh for gas turbines (GTs) and (2) b + fh for baseload plant. Let H be the number of hours of operation which denote the crossover point for which GT and baseload plant total costs are equal. Then, a + eH = b + fH, which yields H = (b − a)/(e − f). The most economic use of plant can be determined by examining the LDC, Figure 14.10, OABCEF. For planned base load operation (i.e. more than H hours per year), X kW of base load plant are used; and for planned peak operation (i.e. fewer than H hours per year), (Y – X) kW of GTs are used. The total annual costs of meeting demand is are given by C0 ¼ Xðb þ fTÞ þ ðY XÞða þ eHÞ: Case 1: Only peak-period demand increases by 1 kW (area AGNB) The optimal system planning response is to increase GT by 1 kW. Total annual costs are given by C1 ¼ Xðb þ fTÞ þ ðY þ 1 XÞ ða þ eHÞ; and the cost rises by C1 − C0 = a + eH. Since this cost increase is caused by the 1 kW rise in incremental demand in the peak period, peak users must pay this cost: capacity charge = a/ kw/yr and energy charge = ekWh. The peak-period users’ payment = a + eH = increase in system costs. Case 2: Only off-peak demand increases by 1 kW (area CIJE). The optimal system planning response is to add 1 kW more of baseload plant. But now there is 1 kW less of GT required than before. The total annual costs are given by C2 ¼ ðX þ 1Þ ðb þ fTÞ þ fY ðX þ 1Þg ða þ eHÞ: Then the increase in cost is given by C2 C0 ¼ ðb þ fTÞ ða þ eHÞ ¼ ðb aÞ þ ðf eÞH þ f ðT HÞ:

496


Substituting for H yields C2 C0 ¼ ðb aÞ þ ðf eÞðb aÞ=ðe f Þ þ f ðT HÞ ¼ f ðT HÞ: Thus, the increase in system cost incurred due to the 1 kW increase in marginal off-peak demand equals the energy cost of operating the baseload plant during this period. Therefore, off-peak users must pay only this energy charge, f/kWh. No capacity costs are charged to off-peak users, since their payment f(T − H) exactly equals the increased system cost. We note that the baseload capacity cost, b, is exactly offset by the total cost saving due to GT, which is no longer required (i.e. capacity cost a plus net fuel cost saving (e − f)H inside area LKIC) in Figure 14.10. In other words, peak capacity cost ¼ baseload capacity cost net fuel savings or a ¼ b ðe f ÞH: Case 3: Both peak and off-peak demand increase by 1 kW This case is a linear combination of Cases 1 and 2. User charges are given by peak capacity charge ¼ a=kW=yr; peak energy charge ¼ e=kWh; off-peak energy charge ¼ f =kWh: Again total payment by all users ¼ b þ fT ¼ rise in system cost: These results may be generalized to include more plant types and rating periods.

14.7 Appendix B: Demand analysis and forecasting 14.7.1 Introduction Using electricity as an example, we examine the key reasons for making accurate demand projections. First, the timely and reliable anticipation of energy needs is vital for the whole economy. Second, the expansion of power systems requires many years to plan and implement. Third, system investments are very capital-intensive. If forecasts are too low, shortages may retard development, while the costs of shortages to users are many times the costs of producing the unsupplied energy. However, if forecasts are too high, large amounts of capital with high opportunity costs might be uselessly tied up for long periods. Such costly errors may be avoided by undertaking relatively inexpensive demand studies. The commonly used unit of energy in power system studies is the kilowatt-hour (kWh). The rate of energy per unit time is called power (or capacity), and is measured in kilowatts


497

(kW). Therefore, energy in kilowatt-hours is the product of power in kilowatts and time in hours. The load factor (LF) is the ratio of average to maximum (or peak) kilowatts over a given interval of time. It is important because the size (and cost) of power-system components are determined mainly by their capability to handle peak power flows. Since practically all customers require their maximum kilowatts only during a short peak period during the day, the LF is also a measure of the intensity of capacity use. A load forecast may be made either in terms of the peak power, or the total energy consumed during a given period (e.g. one year). In general, the kilowatt peaks of different customers will not occur simultaneously. The diversity factor for a group of consumers is a measure of the divergence of spreading over time of the individual peak loads, and permits the computation of the combined peak load for the group in terms of the disaggregate peak values. The total kilowatts and kilowatt-hours generated at the source will be greater than the corresponding values consumed because of system losses. Generation losses are mainly for station use, i.e. for driving auxiliary equipment at power plants. Transmission and distribution network losses are resistive losses, including transformer losses. Theft is another type of loss. Load forecasts are made for various time periods. Very short-term demand projections are made on a daily or weekly basis to optimize system operation or schedule hydro units. Shortrun forecasts ranging between one and three years are used in hydro reservoir management, distribution system planning, etc. The time horizon for medium-term demand projections is about four to eight years, which is sufficient to plan for major transmission and generation projects. Long-range demand projections (usually several decades) are most important in long-run system expansion planning, and are relevant for the sustainomics framework. Several methods are used for this purpose, including time trend analysis, econometric multiple-correlation techniques and field surveys.

14.7.2 Time trend analysis and extrapolation Trend analysis is a commonly used approach when relevant historical data on electricity use are available. Past growth trends are extrapolated, assuming that there will be little change in the growth pattern of the determinants of demand such as incomes, prices, consumer tastes, etc. These trends are usually estimated by a least-squares fit of past consumption data against time or by some similar statistical methodology. Depending on the availability of data, they may be estimated either on a global basis for a given area or broken down by user sector (e.g. domestic, industrial, etc.). Ad hoc adjustments may be made to account for known major changes in future demands. For example, the expected demands of large new industrial plants may be identified. This combination of overall trend projection, together with survey-research type-specific adjustments, is frequently used. The advantages of this approach are its simplicity and modest demands on data and analytical skills. Forecasts use available data. The disadvantage is that no attempt is made to explain why certain usage trends were established in the past. The underlying assumption is that the factors that drove consumption changes in the past will continue unchanged in the future. This is a rather limiting assumption, especially in a world in which relative energy prices are changing rapidly.

498


14.7.3 Econometric multiple regression Econometric forecasting methods are more sophisticated, and potentially more accurate. Past electricity demand is first correlated with other variables, such as prices and incomes, and then future demands are related to the predicted growth of these other variables. However, these methods are frequently nothing more than a special form of trend analysis if the projections of the determinants are themselves based on historical trends. Furthermore, it is often difficult to obtain the required time series needed to produce statistically significant results. Data series are often short, incomplete and subject to changes in definition over time. Besides which, statistical significance requires long time-series data, during which the underlying structure of the economy may have changed. Hence, the results may not be accurate, even though they are statistically significant. A key advantage of econometric studies is that they can take a number of important, demand-determining variables, such as price and income, explicitly into account. A specific type of forecasting approach called ‘end-use analysis’ is used, especially for household consumption, based on the numbers and types of electricity-using devices. Residential demand models are usually based on consumer theory in economics (Nicholson, 1978). The direct utility function of a consumer, which indicates the intrinsic value derived from consumption of various goods, may be written as follows U ¼ UðQ1 ; Q2 ;:::; Qn ; ZÞ; where Qi represents the level of consumption of good i in a given time period (e.g. one year) and Z is a vector representing consumer tastes and other factors. The budget constraint is given by n X I pi Qi ; i¼1

p1, p2,…, pn are the prices of these n goods (including electricity) and I is the consumer income. Maximizing consumer utility U subject to the budget constraint yields the set of Marshallian demand functions for each of the goods consumed by the household: Qi ¼ Qi ðP1 ; P2 ;:::; Pn ; I; ZÞ for i ¼ 1;:::; n: For electricity, the above demand function may be simplified: Qe ¼ Qe ðpe ; pk ; p; I; ZÞ; where subscript e denotes electricity, subscript k indicates the substitute form of energy kerosene (e.g. for lighting) and p is an average price index representing all other goods. If demand is homogenous of degree 1 in the money variables (i.e. prices and income), we may write Qe ¼ Qe ðpe =p; pk =p; I=p; ZÞ: Thus, starting from consumer preference theory, we may derive a demand function for electricity that depends on its own price, the prices of substitutes and income, all in real


499

terms. The effects of other factors (Z) may also be explicitly considered. Effects of supply quality on demand are discussed in Munasinghe (1990b) for electricity, Munasinghe (1992b) for water and Munasinghe and Corbo (1978) for telecommunications. The final specification of such an expression could vary widely (Munasinghe, 1992b; Pindyck, 1979; Taylor, 1976). For example, Qe could be household consumption or per capita consumption; the demand function could be linear, or linear in the logarithms of the variables, or in the transcendental logarithmic form, and could include lagged variables; and Z could include supply side-constraints such as access to supply and so on. Analogously, the industrial demand for energy may be derived from production function theory in economics. For example, consider the annual output of a particular firm of industry: X ¼ FðK; L; M; Q1 ;:::; Qn ; SÞ; where K, L and M are inputs of capital, labour and other non-energy materials, respectively; Qi is the input of energy type i; and S is a set of parameters representing other factors, such as technology changes, etc. To avoid the problem of different types of capita, labour, etc., it is necessary to assume weak separability of the inputs K, L, M and Ei = (Q1, Q2,...,Qn), so that each may be represented as an aggregate, with a distinct, composite price index, i.e. pK, pL and pM. Further, in order to determine the minimum-cost mix of capital, labour, materials and energy, we assume that individual energy inputs like oil and electricity are subject to homotheticity. First, the mix of fuels that make up the energy input are optimized, and, in a second step, the optimal amounts of capital, labour, other material inputs and energy are chosen. Production theory seeks to minimize costs of producing some quantity of output X, given exogenous prices of inputs (Shepard, 1953). As in the household case, the solution yields an electricity demand function, normalized with respect to non-energy input prices (PK) as numeraire: Qe ¼ Qe ðp1 =pK ; pM =pK ; pL =pK ;:::; pn =pK ; X=pK ; SÞ: Thus, the demand for electricity at time t is a function of its own price, the prices of energy substitutes and non-energy inputs, output level and other factors S. Many different variables and specifications may be chosen. Similar demand functions could be developed for other end-use sectors (like agriculture and commerce), estimated with econometric techniques, and used to make future demand forecasts. There are several problems with this approach. First, the mechanistic extrapolation of econometric equations into the future often fails to capture structural shifts in demand. Second, it is difficult to separate out short- and long-run effects. Third, data may be unavailable, especially in developing countries. Fourth, estimation procedures that focus on energy prices as demand determinants may not adequately account for the costs, availability, life expectancies and replaceability of energy-using equipment. Fifth, time-series energy prices could be erratic. Sixth, energy may rationed physically (rather

500


than through price), and service quality could vary. Finally, demand elasticities might change significantly over time.

14.7.4 Field surveys Given the limitations of the other forecasting methodologies, surveys potentially provide a direct and reliable tool of demand analysis and forecasting. In essence, surveys consist of a list of more or less sophisticated questions that are put to existing and potential electricity users in order to measure and record their present consumption and future consumption plants. Energy surveys could also be usefully combined with other types of survey, such as general population censuses, income studies, etc. Major problems with surveys are: (a) large time requirement; (b) high cost; (c) need for skilled interviewers; (d) user inability or unwillingness to provide the requested information; (e) user deliberately or unwittingly giving inaccurate answers; (f) future energy use plans may be vague.

14.7.5 Practical application In summary, there is no single universally superior approach to load forecasting. More sophisticated techniques might obscure weak data and methodological assumptions. Thus, simpler methods may be more useful when information is unreliable. Often, the sum of many disaggregate demand forecasts may be compared to an independently made global forecast for the same area. Survey approaches are most effective to forecast the demand of large users. The determinants of demand for diverse users have to be carefully selected because they vary. The level of disaggregation will depend both on the data and the ultimate purpose of the projection. Demand forecasting is dynamic, and requires frequent iteration in light of better data and techniques of analysis. Building a reliable data bank is invaluable in this process of constant revision. An experienced forecaster will be able to make appropriate adjustments, based on judgement, about constraints and complicating factors that cannot be incorporated mechanistically into a numerical forecasting. Load promotion, consumer education and the attitudes of community leaders can also significantly affect demand growth. The demand forecast for a given consumer group will depend on the number of connections the average electricity use per connection and user characteristics. Thus, the evolution of each of these variables needs to be analysed. Connection policy is another key factor. If income levels are low, high connection charges could act as a significant barrier and negate the favourable effects of low electricity prices. Finally, a distinction should be made between the underlying or potential demand and the consumption level that is actually achievable. Practical limitations may prevent the realization of overambitious demand forecasts. Institutional constraints that suppress demand, such as power cuts or nonconnection of consumers and the presence of captive generation, will create a gap between the potential and achievable (or realistic) demand.

Part V Project and local applications

15 Project applications1

Applications of the sustainomics approach at the project level are illustrated in this chapter. In Sections 15.1 and 15.2, the sustainable energy development framework applied at the sector level (Chapter 10) is extended and used to evaluate small hydroelectric power projects in Sri Lanka. Multicriteria analysis is used to assess social, economic and environmental indicators. Section 15.3 highlights the use of different policy tools (including the interplay of shadow and market prices) – to influence human behaviour relating to new and renewable energy use in a typical developing country. Practical investment and pricing policies are formulated to make energy development decisions more sustainable, in the case of solar photovoltaic energy projects for agricultural pumping. In Section 15.4, rural electrification projects in Sri Lanka are analysed, focusing on new and renewable energy technologies. Rural energy priorities (solar homes and village hydro) in Sri Lanka are compared with renewable energy projects in the Philippines and Vietnam. Section 15.5 presents a case study involving the analysis of a project that supplies water to a poor African village, by drilling wells and boreholes. The focus is on quantitative economic cost–benefit analysis, using both border and domestic shadow prices to determine water-investment decisions and pricing policy.

15.1 Small hydro-projects and sustainable energy development in Sri Lanka Energy is a key resource which affects the economic, environmental and social dimensions of sustainable development (see Chapter 10). Further, hydroelectricity is a key renewable source of energy that contributes toward sustainable energy development (UNEP, 2000). Accordingly, this case study illustrates the application of sustainomics principles (e.g. using multicriteria analysis) to assess the economic, social and environmental impacts of hydropower projects in Sri Lanka. The case study is presented in three parts. Section 15.1.1 describes the power sector in Sri Lanka and the transition from a predominately hydro to a mixed hydrothermal system.

1

The valuable contributions of R. Morimoto and P. Meier to this chapter are gratefully acknowledged. Some parts of the chapter are based on material adapted from Morimoto and Munasinghe (2005), Munasinghe (1977, 1983) and Munasinghe and Meier (2003b).

503

504

Project and local applications

Section 15.1.2 sets out the methodology. The results are analysed in Section 15.2, and are followed by some key conclusions.

15.1.1 Brief review of the Sri Lanka power sector Growth rates of GDP and electricity demand in Sri Lanka are well correlated – see Figure 15.1 (CEB, 1999, 2003). The Pearson correlation is 72% (1% significance level). Electricity use fell sharply in 1996 and 2001, due to serious droughts and hydro shortages, which also lowered GDP growth (−1.5% in 2001). The demand for electricity in Sri Lanka is increasing very rapidly. In 2003, the maximum electricity demand was 1422 MW, and this is expected to double every ten years (CEB, 2003). Currently, Sri Lanka depends largely on hydropower for power generation (Figure 15.2). In 1998, over 60% of energy demand (3351 GWh) was met by hydropower, about 30% (1599 GWh) by thermal power, and less than 5% (159 GWh) through self-generation (CEB, 1999). However, hydrogeneration share has fallen since then. In 2002, hydropower met only about 39% of the demand, whereas the thermal share had increased to 60%, while self-generation had declined to 1%. By 2003, over 1200 MW of major hydro had been developed, to provide about 3858 GWh of energy in an average year (CEB, 2003). The CEB will install a 300 MW coal plant by 2011, as well as more oil-fired plant. Thus, Sri Lanka is now in a transitional period, moving from a predominantly hydropower system to a mixed hydrothermal power system, using imported oil and coal. In 2003, the electrification rate in Sri Lanka was 66%, and the majority of the rural population did not have access to electricity (Department of Census and Statistics, 2003). The target electrification rate of the government for 2006 was 77% (CEB, 2003). About 400 000 homes without access to electricity use automobile batteries to power lamps, radios and TVs. Others use kerosene for lighting and firewood for cooking.

GDP growth rate

7.00 6.00

GDP electricity

15.00

5.00 4.00

10.00 5.00

3.00 2.00

0.00

1.00 0.00

–5.00

–1.00 –2.00

electricity demand growth

20.00

8.00

1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

–10.00

year

Figure 15.1. GDP and electricity demand growth rates in Sri Lanka. Source: Central Bank (1998, 2003), CEB (1999, 2003).

15 Project applications

505

8 generation (GWh)

7 6 5 4 3 2 1 0 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 year hydro

thermal

self

Figure 15.2. Hydrothermal energy share in Sri Lanka. Source: CEB (1999, 2003).

Renewable energy sources will provide only a fraction of Sri Lanka’s power needs in the coming years. However, mini-hydro, solar, wind and biomass (including dendro-thermal) are drawing more attention, since they could play a key role in sustainable energy development (see Section 15.7).

15.1.2 Methodology Multicriteria analysis (MCA) is used in order to examine the impacts of hydroelectric projects and make development more sustainable in this study. MCA is a powerful tool to quantify and display the trade-offs that must be made between conflicting objectives that are difficult to compare directly (see Section 3.5). The MCA approach provides decision makers with useful additional information to supplement the economic data from cost–benefit analysis (CBA). Three main sustainable development issues considered comprise the economic costs of power generation, ecological costs of biodiversity loss and social costs of resettlement. The main objective is to generate additional kilowatt-hours of electricity to meet the growing power demand in Sri Lanka. We compare the sustainable development impacts of power projects on the basis of the economic, social and environmental costs of generating one unit of electricity from various hydro sites, assuming that the same benefit from each additional kilowatt-hour. With MCA, social and environmental impacts are measured in non-economic units, instead of monetarily valuing and incorporating them within the singlevalued CBA framework. Economic indicator – power-generation costs The usual economic indicator in project evaluation is the maximization of net present value (NPV). However, in this study, minimizing average generation costs per unit of

506


generation will be used as the main economic comparator instead of NPV – assuming that the total benefit per unit generated is the same for all projects under comparison (see Section 3.2.1). If we wish to rank two projects according to the net benefit per unit of electricity generated, then project 1 will be better than project 2 if NB1 =Q1 4 NB2 =Q2 ;

(15:1)

where NBi = (Bi – Ci) = net benefit; Qi = quantity of electricity generated; Bi = total benefit; and Ci = total economic cost, of project i. Then, the following assumption may be made: B1 =Q1 ¼ B2 =Q2 :

(15:2)

This is a reasonable approximation, since one unit of electricity will produce the same total benefit within the electricity grid, irrespective of the source of generation (if transmission costs to connect generators to the grid are equal). Thus, equation (15.1) can be expressed as follows: ðC 1 =Q1 Þ4ðC 2 =Q2 Þ:

(15:3)

We may interpret equation (15.3) to mean that the project with the lower cost per unit of electricity generated is preferred. Cost Ci is estimated as the present discounted value of project costs (10% discount rate), annuitized over the project lifetime, while Qi would be the average expected generation per year. In this illustrative case study, we have focused on energy generated by assuming equal plant factors and we have ignored capacity considerations. Hence, average generation costs per year are used as the economic indicator of sustainable energy development. Environmental indicator – biodiversity index In electric-power-plant evaluation, detailed site-specific environmental data are unlikely to be available at the long-range system planning stage. Thus, the quantification of biodiversity impacts that is possible at this level of aggregation is a probabilistic estimate that gives decision makers advance warning about the likelihood that a more detailed environmental impact assessment will reveal adverse effects on an endemic species, significant ecosystems impacts, or degradation of a habitat already in a marginal condition (see Chapter 4). Although endemicity and biodiversity are not necessarily correlated, endemic species in Sri Lanka are most likely to be encountered in areas of high biodiversity. A biodiversity index must reflect several key characteristics. First is the nature of the impacted system itself. In Table 15.1, the main agroecological zones encountered in Sri Lanka are ranked and assigned a value (wj) that captures the relative biodiversity value of different habitats. The scale is a strict ratio scale (i.e. zero indicates a zero amount of the characteristic involved, and a value of 0.1 implies ten times the value assigned to a value of 0.01). The second element concerns the relative valuation, because the value of the area lost


507

Table 15.1 Biodiversity index values of Sri Lankan agroecological zones Rank

Ecosystem

Relative biodiversity value

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

lowland wet evergreen forest lowland moist evergreen forest lower montane forest upper montane forest riverrine forest dry mixed evergreen forest villus mangroves thorn forest grasslands rubber lands home gardens salt marshes sand dunes coconut lands

0.98 0.98 0.9 0.9 0.75 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.01

Adapted from Meier and Munasinghe (1994).

is a function of the proportion of the habitat that is lost. For example, the loss of the last hectare of an ecosystem would be unacceptable, and hence assigned a very large value (even if it had a low biodiversity, such as a sand dune), whereas the loss of 1 hectare out of 10 000 would be much less valuable. The total biodiversity index value associated with site i is defined as follows: X Ei ¼ wj Aij ; (15:4) j

where Aij denotes the number of hectares containing an ecosystem of type j at site i and wj is the relative biodiversity value of type j (as defined in Table 15.1). Since Ei may be correlated with reservoir size (i.e. inundated land area and energy storage capacity), two further scaled indices are defined: X F i ¼ Ei = Aij ¼ Ei =ðtotal land area affected at site iÞ (15:5) j

and Gi ¼ Ei =ðhydroelectric energy generated per year at site iÞ:

(15:6)

Thus, Fi is the average biodiversity index value per hectare of affected land and Gi is the average biodiversity index value per unit of energy produced per year. These formulae are applied to each hydro site to determine the biodiversity index value and are used as the environmental indicator of sustainable energy development.

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Social indicator – resettlement Although dam sites are usually in less densely populated rural areas, resettlement is still a serious problem. In general, people are relocated from the wet to the dry zone in Sri Lanka (where soils are less rich), and therefore the same level of agricultural productivity cannot be maintained. In the wet zone, multiple crops including paddy, tobacco, coconuts, mangos, onions and chilies can be grown. However, these crops cannot be cultivated as successfully in the dry zone, due to limited water and poor soil quality. Living standards often become worse and problems (like malnutrition) could occur. Moreover, other social issues, such as erosion of community cohesion and psychological distress due to change in the living environment, might arise. Hence, minimizing the number of people resettled due to dam construction is an important social objective. Thus, the number of resettled people per year per unit of energy produced is used as the social indicator of sustainable energy development.

15.2 Main findings of small hydro study 15.2.1 Analysis of results Table 15.2 lists the 22 hydro-projects in Sri Lanka used in this study (CEB, 1987, 1988). The size of the hydro-projects varies from 10.9 to 512 GWh/yr. All three variables used (i.e. generation costs, biodiversity index and number of resettled people) are given per unit of electricity produced, which scales by project size and makes them comparable. In Figure 15.3, the values of each criterion are provided for all 22 projects. Clearly, on a per kilowatt-hour per year basis, the project AGRA003 has the highest biodiversity index, HEEN009 has the highest number of resettled people and MAHA096 has the highest average generation cost. Table 15.2 shows that small hydro-projects tend to have high unit generation costs, while larger projects appear to have more resettlement. The impact on biodiversity provides a more mixed picture. More generally, ranking projects according to each criterion separately on the basis of Figure 15.3 does not provide a clear basis for making decisions. Small hydro-projects (say up to 10 MW) can become more favourable economically if present technology trends continue to reduce average generation costs. Larger hydroprojects would gain more favour if the scale of resettlement is controlled and reduced. In order to reduce the impacts of hydropower development on biodiversity, careful considerations and studies would be needed for the location of dam sites. Some important comparisons may be made using Figure 15.3. For example, KALU075 is a relatively large project, where costs are low, whereas MAHA096 is a smaller scheme with much higher costs with respect to all three sustainability indices. Further, a project like KELA071 fully dominates GING053, since the former is superior in terms of all three indicators. Similar comparisons may be made between other projects. There is a little correlation between quantity of


509

Table 15.2 Description of the hydropower projects in Sri Lanka Project number

Project name

River basins

Electricity generated (GWh/yr)

1 2 3 4 5 6 7 8 9 10a 11 12 13 14 15 16 17 18 19 20 21 22

AGRA003 DIYA008 GING052 GING053 GING074 HEEN009 KALU075 KELA071 KOTM033 KUKU022 LOGG011 MAGA029 MAGU043 MAHA096 MAHO007 MAHW235 MAHW287 NALA004 SITA014 SUDU009 SUDU017 UMAO008

Agra Oya Diyawini Oya Ging Ganga Ging Ganga Ging Ganga Heen Ganga Kalu Ganga Kelani Ganga Kotmale Oya Kukule Ganga Loggal Oya Magal Oya Maguru Oya Maha Oya Maha Oya Mahaweli Ganga Mahaweli Ganga Nalanda Reservoir Sitawaka Ganga Sudu Ganga Sudu Ganga Uma Oya

28 10.9 159 210 209 19.9 149 114 390 512 22 77.8 161 33.5 50 83.4 42.2 17.9 123 79 113 143

a

Since KUKU022 is a multipurpose project, some non-power benefits may be excluded. Source: CEB (1987, 1988).

electricity generated, average generation cost, the number of resettled people and the biodiversity index. Figure 15.4 shows sustainable development indicators for these hydro sites in three dimensions, with the axes representing economic ecological and social objectives, respectively. The distance from the origin to each coordinate point is critical. Generally, the closer to the origin, the better the project is in terms of achieving the three objectives. As explained in Chapter 3 (see Figure 3.6), projects that are superior to others on the basis of all three indicators will define a non-inferior (or trade-off) surface. In the case of Figure 15.4, hydro-projects on such a surface will dominate all others lying outside and more distant from the origin, whereas the opposite is true for Figure 3.6 (since the directions of the axes are reversed). Next, choosing among the projects on the trade-off surface will need further definition of relative weights to be assigned to the respective objectives. This kind of three-dimensional figure gives a visually clearer view of hydro-projects in terms of the three sustainable development indicators than a simpler two-dimensional figure, such as

510

Project and local applications 20 AVC (US cents ( kWh/yr)) BDI (kWh/yr) RE (kWh/yr)

18 16 14 12 10 8 6 4 2

DI

AG

RA

00 YA 3 GI 00 NG 8 GI 05 NG 2 GI 053 N HE G07 E 4 KA N00 LU 9 KE 07 L 5 KO A0 T 71 KU M0 KU 33 LO 02 G 2 M G0 AG 1 1 M A0 AG 29 M U0 AH 43 M A0 AH 96 M O0 AH 07 M W2 AH 35 NA W2 LA 87 SI 004 T SU A01 D 4 SU U00 D 9 UM U0 1 AO 7 00 8

0

project

Figure 15.3. Average generation costs (AVC), biodiversity index (BDI) and number of resettled people (RE) by hydro-project. All indices are per kilowatt-hour per year. Generation costs are calculated using a 10% discount rate. Numbers of people resettled and the BDI are scaled for convenience (by the multipliers 10–5 and 10−9, respectively). Source: CEB (1987, 1988); Meier and Munasinghe (1994).

Figure 15.3. Hence, it provides policy makers with a better idea about which project is more favourable from a sustainable energy development perspective. For illustrative purposes, we arbitrarily give all three objectives an equal weight, assuming that all of them are equally important for sustainable energy development. Then, each project may be ranked by its absolute distance from the origin, given by distance ¼ ½ðx-coordinateÞ2 þ ðy-coordinateÞ2 þ ðz-coordinateÞ2 1=2 : For example, rank 1 is given to the one closest to the origin, rank 2 is the second closest, etc. This ranking makes visual comparison of projects easier, although a different weighting scheme could change the rankings. From this overall sustainable energy development perspective, the most favourable project is GING074 (rank 1), whereas the least favourable is MAHA096 (rank 22) – see Table 15.3 (final column). Table 15.3 also shows a more complete set of rankings, where the three objectives are considered two at a time. For economic–ecological, economic–social, and ecological–social indices, GING074 has rankings of 1, 2 and 7, respectively. This indicates that it is also quite a balanced project from a sustainomics viewpoint. Thus, this


511

economic indicator, AVC (kWh/yr)

6

18.4 17.7 16.8 16.4 15.3 12.6 12.1 12.0 11.1 9.8 9.7 8.8 8.6 7.8 7.6 7.2 7.1 5.8 5.1 4.3

14

15

4 2

11 3

17

13 1

20 7 12

19 10 21

9

16 8

8

22 5

0.00 social

2.50 indica to

5.00

r, new

7.50

RE (k

Wh)

10.00

0.00

5.00 4.00 tor, a 2.00 indic ental ) m h n o W envir DI (k new B

Figure 15.4. Three-dimensional graphical analysis of impact on sustainable development.

approach seems to provide more intuitively appealing and robust results when policy makers wish to make their decisions.

15.2.2 Conclusions Sri Lanka has moved in recent decades from a predominantly hydroelectric system to a mixed hydrothermal system. Renewable sources of energy are a key factor in successfully achieving the transition to sustainable energy development. MCA has been used to assess the impact of hydro-projects on sustainable energy development. The strength of this type of analysis is in helping policy makers to compare project alternatives more easily and effectively. The simple graphical presentations more clearly identify the sustainable development characteristics of each scheme. MCA supplements the more conventional CBA, based on economic analysis alone. Since each project has different features, assessing them by looking at only one aspect (e.g. generation costs, effects on biodiversity or impacts on resettlement) could be misleading. Together, with more detailed analyses for each hydro-project, this type of graphical MCA could be a useful tool for project assessments. There are several possible improvements that could be made in the MCA approach used here. First, for simplicity each major objective is represented by only one key variable. In reality, there may be more than one variable that describes the economic, social and environmental aspects of sustainable development. Further analysis that includes other

512


Table 15.3 Rankings of projects based on any two objectives and overall (arbitrary equal weighting of indicators) Project Number

Project name

Economic– ecological

Economic– Ecological– Overall ‘3D MCA’ social social (Figure 15.4)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

AGRA003 DIYA008 GING052 GING053 GING074 HEEN009 KALU075 KELA071 KOTM033 KUKU022 LOGG011 MAGA029 MAGU043 MAHA096 MAHO007 MAHW235 MAHW287 NALA004 SITA014 SUDU009 SUDU017 UMAO008

13 18 19 21 1 22 7 15 4 12 16 5 4 20 17 6 10 2 8 10 8 2

22 17 13 20 2 19 14 15 5 7 17 6 8 21 16 4 11 3 12 10 9 1

22 14 16 20 7 19 13 18 5 14 17 4 10 21 2 8 3 1 12 9 11 6

19 17 15 20 1 21 13 9 4 6 16 8 12 22 18 5 14 3 10 11 7 2

variables may provide new insights. Second, a possible extension of this study is to analyse other renewable sources of energy. Third, the choice of discount rates could affect the calculations and rankings relating to the economic variable. Fourth, exclusionary screening techniques (i.e. eliminating dominated projects like GING053, and focusing only on nondominated ones) may provide a clearer picture. Finally, better three-dimensional graphic techniques may yield a clearer representation (Tufte, 1992).

15.3 New and renewable energy projects: case study of solar photovoltaics Modern societies require increasing amounts of energy for domestic, industrial, commercial, agricultural and transport uses. Arrayed against these energy needs are short-term, depletable fossil-fuel supplies (oil, coal and natural gas), as well as the longer-run, renewable energy sources, like hydro, solar, geothermal, wind, tidal and biomass. Commercial forms of energy, such as electricity, oil, coal and gas, have dominated the world energy scene. However, rising oil prices and environmental problems (including climate


513

change) associated with fossil-fuel use have increased the attractiveness of renewable-energy sources. The potential for biomass-based energy is indicated by the fact that the total world use of energy in the early 1990s was less than one-fifth of the annual photosynthetic conversion of sunlight via biomass. In 2003, renewables accounted for 13% of the 10 579 megatonne of world total primary energy supply (TPES) – see also Section 10.2.3. Combustible renewables and waste (97% biomass) represented about 80% of total renewables and 16% of hydro. Total renewables supply grew annually at 2.3% during 1971–2003 – marginally higher than the annual growth in TPES. However, ‘new’ renewables like geothermal, solar, wind, etc., had a much higher annual growth of 8%. Starting from a low base in 1971, wind experienced the highest annual growth rate (49%), followed by solar (29%) (IEA, 2005). Asia, Africa and Latin America are the main renewables users, with most of the use occurring in homes for cooking and heating. OECD accounted for 47% and 67%, respectively, of the use of hydro and other (or ‘new’) renewables (solar, wind) in 2003. A consistent methodology based on sustainomics principles is outlined below, to make small or decentralized energy projects development more sustainable, by analysing and correcting for distortions in financial prices. The latter would lead to economically inefficient allocation of resources as well as environmental and social harm. The principles underlying this framework are also applicable to other large-scale public investment projects in the energy sector, but here the analysis has been adapted to meet the special difficulties that arise in the evaluation and implementation of the new and renewable technologies. Section 15.3.1 outlines the methodology, including economic criteria for accepting a new technology (based on shadow prices and the national viewpoint), the financial requirements for successful implementation (based on market prices and the private viewpoint) and policy implications of this analysis. Finally, a case study involving solar photovoltaic water pumping (for irrigation) is presented, to show how economic and financial analyses could interact to make national energy policy more sustainable.

15.3.1 Economic and financial methodology This approach focuses on the sector-project level of the sustainable energy development framework (see Figure 10.4). The basic steps for making and implementing an investment decision involving rural energy sources, as well as the underlying economic and financial criteria are shown in Figure 15.5. Consider a decentralized rural energy source, which we identify as technology R. First, it is important to establish the existence of a demand or market for energy services of the type to be provided by technology R. For example, the use of kerosene for lighting in rural areas indicates that there is a potential market for an alternative energy source, such as local small-scale hydro plants or diesel generators, to provide the same service. The second step involves choice of the least-cost technology based on the national viewpoint. Shadow prices (or economic opportunity costs) are used to determine whether technology R is cheaper than alternative means of providing the same energy services (see Chapter 3). If technology R is not least-cost, it is rejected and we proceed no further with the analysis.

514

Project and local applications investment

reject economic choice of least-cost technology (national viewpoint – shadow prices)

reject

economic CBA (national viewpoint – shadow prices)

accept

accept demand for energy services

national pricing and other policy adjustments

implementation programme

reject financial choice of least-cost technology and its profitability (private viewpoint)

accept

implementation feasibility

Figure 15.5. Principal steps in economic and financial analysis for investment decision and implementation.

If technology R is accepted on a least-cost basis, an economic CBA is required to confirm the investment decision. The benefits derived by using technology R are compared with the project costs, once again using shadow prices. Environmental impacts and other externalities, which may be valued in economic terms, are included in the analysis (see Chapter 3). If costs exceed benefits, the project is rejected and goes no further. If net benefits (i.e. benefits minus costs) are positive, then technology R is acceptable from the national viewpoint and the decision to invest is economically justified. The next stage in the analysis tests the feasibility of project implementation. If the project is to be financed and built by the government (e.g. small-sale hydro plant to provide rural electricity), then the pricing of the output is a key issue. Basically, it should be verified that the demand for the energy service would still exist at the market or financial price to be charged to the user. As described in Chapter 14, this price should generally reflect the marginal economic opportunity cost (or long-run marginal cost) of supply, to meet the economic efficiency objective. The energy-pricing policy would also be modified by sector financial viability considerations, socialsubsidized or lifeline pricing needs of poor consumers and other constraints and national goals. The analysis of financial feasibility is more complicated in the case of a project involving a decentralized technology such as solar photovoltaic (PV) powered electric pumps for farm use,


515

which is essentially purchased or paid for by private individuals who are the ultimate beneficiaries. In Figure 15.5, two financial tests seek to verify from a private individual’s viewpoint, using market prices, whether technology R is (i) cheaper than any alternative method of meeting the same need and (ii) profitable, i.e. whether the benefits derived from using technology R outweigh the costs. In an ideal distortion-free economy, market prices and shadow prices are identical, and the economic and financial tests of the project would yield the same answer (see Box 2.3 and Chapter 3). In practice, market prices diverge significantly from shadow prices, and therefore both economic and financial calculations have to be carried out separately. If technology R is financially least-cost and profitable, it is clear that rational private individuals would adopt the technology. Thus the government and private investment decisions coincide, and the project implementation programme can begin. If an economically justifiable project fails one or both of the financial tests, then the government must seek to adjust market prices or other policies to make the new technology more financially attractive to private individuals. For example, a competing technology may be financially cheaper because the market price of fuel is subsidized. The required policy change then might be to remove the fuel subsidy, thus making the alternative technology more expensive, or to ban the latter altogether through legislation. The rationale underlying the policy changes is that the government should manipulate the market environment to make technology R financially attractive. Thus market prices would be brought more in line with shadow prices by eliminating taxes and subsidies, and legislative and physical controls would also be brought into play, as appropriate. Such policy changes will not affect shadow prices significantly, so economic acceptability of the project from the national perspective would be unchanged. When the project passes both the economic and financial tests, the implementation programme may begin.

15.3.2 PV energy for agricultural pumping The economic evaluation of a decentralized new energy technology such as the PV irrigation pumping system discussed in the following, and the decision to implement this technology, illustrates the close interaction between the economic and financial analyses in policy making. The example and numbers selected are purely illustrative, and do not necessarily prove the superiority of one technology. The economic analysis is based on the cost–benefit criteria and efficiency shadow pricing (see Chapter 3). We assume that the agricultural area under consideration is so remote that electrification via the main power grid would be too costly. The main competitor of PV systems in this case is the diesel pump. To compare these two discrete alternatives, we look only at a single representative farm, and we analyse both economic and financial data. Consider a typical 1 hectare farm that requires about 20 m3/day of water, with a head of 5 m. Since the benefits are identical in both cases, we first determine the least-cost alternative by comparing diesel and PV system costs. The basic data for a simplified hypothetical example are shown in Table 15.4. In actual practice, a range of parameters (e.g. different farm sizes, insolation rates, cropping patterns, system costs, etc.) may have to be considered.

516


Table 15.4 Basic data for solar PV and diesel pumping systems Solar PV Market prices (DRs) Initial cost 66 000 Annual maintenance costs 1100 Annual fuel costs – Lifetimeh (yr) 10 Discount rate (%) 15f Annual inflation rate (%) 10

Diesel

Shadow prices (BRs)a

Market prices (DRs)

Shadow prices (BRs)a

60 000 1000b – 10 10g –

28 800 1500 840e 5 15f 10

36 000c 1050d 1200 5 10g –

a

All foreign costs converted into border rupees (BRs) at official exchange rate of US $1 = Rs 20. All foreign exchange costs with 10% import duty. c Import subsidy of 20% on diesel pumps provided to farmers. d Conversion factor = 0.7 based on spare parts and labour. e Subsidy of 33% provided on diesel fuel imported at US $3/1itre, and international fuel price assumed to rise at 3% per annum in real terms. f Bank borrowing rate for farm loans. g Opportunity cost of capital used as proxy for the accounting rate of interest (ARI). h Solar PV is assumed to be inherently more longer lived. b

15.3.3 Investment decision We compare the present value of costs (PVC) of the two alternatives over a ten-year period, in economic efficiency shadow prices. The monetary unit (numeraire) is the border rupee (BRs), equivalent to US $0.05. Solar:

PVCSE ¼ 60 000 þ

9 X

1000=ð1:1Þt

t¼0

¼ BRs 66 760: Diesel:

PVCDE ¼ 36 000 þ 36 000=ð1:1Þ5 þ

9 X ½1050=ð1:1Þt t¼0

þ 1200ð1:03=1:1Þt ¼ BRs 74 540:

For diesel, the real fuel price increase of 3% per annum will partly offset the effect of discounting at the opportunity cost of capital of 10%. The above results show that the solar PV system is the least-cost alternative. Next, assume that, due to the increased irrigation, the shadow-priced value of farm annual output of grain increases from BRs 10 000 to BRs 20 500/hectare, based on the export price of grain. This increase in output value is net of any changes in costs of other inputs such as


517

Table 15.5 Economic and financial tests for investment decision All amounts are in present value terms

Item

Solar PV costs Diesel costs Irrigation benefits

A

B

C

D

National viewpoint: shadow prices (BRs)

Private viewpoint (initial) market prices before policy changes (DRs)

Private viewpoint (interim): market prices after first policy change (DRs)

Private viewpoint (final): market prices after second policy change (DRs)

PVCSE = 66 760 PVCDE = 74 540 PVBF = 78 000

PVCSF = 75 080 PVCDF = 71 110 PVCE = 70 970

PVCSF = 75 080 PVCDF = 85 070 PVBF = 73 670

PVCSF = 75 080 PVCDE = 86 070 PVBF = 73 670

fertilizer and labour. Then the present value of benefits (PVB) for the ten-year period is given by PVBE ¼

9 X

ð20 500 10 000Þ=ð1:1Þt

t¼0

¼ BRs 70 970: Since NPV = PVBE – PVCSE = BRs 4210, there is a positive net benefit to the country by installing solar PV pumps in farms (see column A of Table 15.5). Thus, from a national viewpoint, the government is justified in taking a policy decision to encourage use of solar PV systems by farmers.

Box 15.1 Conclusion Condition (columns A to D, Table 15.5) Consequences A: Shadow-priced values PVCSE < PVCDE Solar PV is the economically preferred least-cost technology PVBE > PVCSE Investment in solar PV is economically justified B: Market-priced values before policy changes PVCSF > PVCDF Financially, farmers will prefer diesel to solar PV pumps C: Market-priced values after first policy changes Financially, farmers will prefer solar PV to diesel pumps PVCSF < PVCDF PVBF < PVCSF Farmers will find solar PV pumps financially unprofitable D: Market-priced values after second policy changes PVCSF < PVCDF Financially, farmers will prefer solar PV to diesel pumps PVBF > PVCSF Farmers will find solar PV pumps financially profitable

518


15.3.4 Implementing the investment policy Irrespective of government decisions, farmers will make their irrigation pumping decisions on the basis of private financial costs and benefits. Therefore, we analyse the present value of costs of solar and diesel systems in financial terms, using market prices (domestic rupees, DRs). Solar: PVCSF ¼ 66 000þ

9 X

1100ð1:10=1:15Þt ¼ DRs 75 080:

t¼0

Diesel: PVCDF ¼ 28 800 þ 28 800ð1:10=1:15Þ5 þ

9 X ½1500ð1:10=1:15Þt t¼0

þ 840ð1:03 1:10=1:15Þt ¼ DRs 72 110:

Since PVCSF > PVCDF, the average farmer would prefer to buy a diesel pump rather than a solar PV system. Because the market price signals are distorted, the private individual’s decision does not coincide with the national policy decision based on shadow prices (column B of Table 15.5). Therefore, the government must adjust the market prices, or adopt other policies that will make the solar PV option attractive to farmers. First, authorities could remove the 10% import duty on solar PV systems. Then PVCSF = DRs 68 250, and solar PV pumps become the least-cost alternative both financially and economically. However, this measure may also require reduction of import duties on many similar PV and electric components, which the government is unwilling to consider. A second policy option is to raise diesel fuel prices until PVCDF exceeds PVCSF – but this may be blocked by a strong anti-inflation lobby on the grounds that it would raise transport costs too much. A third choice might be for the government to legislate that farmers could no longer buy diesel pumps. This non-price policy option is cumbersome and has its own implementation problems. A fourth possibility is for the government to provide low-interest agricultural loans or credits to buy solar pumps. Finally, the government could remove the import subsidy on diesel motors. This increases PVCDF to DRs 85 070, which exceeds PVCSF. Then, farmers will voluntarily prefer solar PV pumps to diesel pumps. We assume that this policy option is selected (column C of Table 15.5). It is still necessary to consider the financial benefits aspect. The irrigation programme increases the market value of farm output from DRs 8 500 to DRs 17 425, based on the guaranteed government purchase price for grain (which is 85% of the export or world market price). The present value of financial benefits for ten years of output is given by PVBF ¼

9 X

ð17 425 8500Þ ð1:10=1:05Þt

t¼0

¼ DRs 73 670: Since PVBF is less than the value PVCSF = DRs 75 080, the average farmer will be financially worse off if he adopts the (least-cost) solar PV technology. Then, the government


519

must make a further change in policy. For example, it could raise the domestic grain price to 90% of the world price. This policy change raises the value of financial benefits, and since PVBF = DRs 78 000 > PVCSF, the farmer will find solar PV powered pump sets financially profitable to install (column D of Table 15.5). This case study shows that demand management via implementation of a given investment decision (based on shadow prices) could help to make renewable energy development more sustainable. However, it would require a related series of wide-ranging policy decisions by the government.

15.4 Sustainable rural electrification based on renewable energy This section discusses rural electrification (RE) projects based on renewable energy. Due to the high costs involved, we focus on the sustainability of economic and financial aspects. RE is important for poverty reduction. As in most developing countries, poverty is largely a rural phenomenon in Sri Lanka – a 1996 survey concluded that 88% of the poor live in rural areas, compared to 8% in urban areas and 4% in estate areas (Nexant, 2004). At the end of 2002, only 63% of homes in Sri Lanka had power, with electrification rates ranging from 87% in the Colombo district to 32% in Moneragala. Electricity access and poverty are highly correlated (see Figure 15.6). The higher the poverty rate, the lower the electrification rate. The data shown do not include unsettled districts in the northern and eastern areas, where poverty rates are substantially higher and electrification rates are lower. Off-grid schemes account for a small but growing fraction of household electrifications. In 2003, about 28 000 homes had PV solar home systems and 3000 homes were supplied by village-scale hydro systems. These off-grid options are two key components of the Energy Services Delivery (ESD) programme (the other components included a 3 MW wind demonstration programme and grid-connected small hydro), discussed in the following. We begin with a discussion of the key issue of how the benefits of rural electrification are to be quantified.

Electrified households (%)

100 Colombo Gampaha

80

Galle Kalutara Matara Kandy

60

Badulla Puttalam Kurunegala Anuradhapura Polonnaruwa Ratnapura Hambantota

Kegalle Nuwara Eliya

40

Moneragala

20

0

20

40 poverty (%)

60

80

Figure 15.6. Electrification and poverty for selected districts. Based on data in Nexant (2004) and from Sri Lanka Central Bank.

520


15.4.1 Measuring economic benefits of rural electrification There are two basic methods for estimating economic RE benefits (Munasinghe, 1987). The first is to set benefits equal to the avoided costs of the various means, presently used to supply energy, which would be replaced by the mini-hydro scheme – including kerosene, diesel generation for battery charging and productive uses, candles and dry cells. This ‘avoided cost’ method is easily applied because the data can be provided from surveying existing households and the calculations are straightforward. However, the method generally underestimates the actual benefits. First, the quality of energy supply from electricity is far superior to that from most alternative devices. For example, the illumination from a compact fluorescent lamp (CFL) is much higher than that provided by candles or kerosene lamps. Individuals are prepared to pay more for high-quality service because they value a given number of lumens from electric light bulbs much more than the equivalent number of lumens from candles and kerosene. In other words, the benefits are greater than those that may be inferred from replacement costs alone. Electric lighting also avoids many other harmful side-effects (such as smoke and odour, risk of fire and injury). In Sri Lanka, 50% of burn injuries are attributable to accidents involving kerosene lanterns and candles. Similar problems are reported in other countries (Foster and Tre, 2000; Reyes, 2001). This is an important area for further research, because burn injuries and child deaths have high social costs, whose avoidance should be counted as one of the benefits of rural electrification in general (and solar PV systems in particular). Such direct costs may be easier to ascertain than those related to local air pollution. Second, as shown in Figure 15.7, the demand curve (which shows the quantity demanded as a function of price) for electricity services is downward sloping, while the total benefits of

price A Pkero B* PKE B C PEE PE PES

D*

E*

D

E

T

S

QE

Qkero service level

Figure 15.7. Demand curve for electricity services and reconciliation of economic and financial flows.


521

electricity consumption are given by the area under that curve (see Section 3.3.2). It is well established that individuals are prepared to pay very high prices for the first few kilowatthours of electricity (or lumens), sufficient for one or two CFLs. They are also prepared to pay high prices for enough electricity to power a TV. But the amount they are prepared to pay for subsequent CFLs will be less than the first CFL (which replaced candles or kerosene). An alternative approach to calculating benefits requires estimation of such a demand curve. This is generally more difficult, because there the data may not be available to determine the shape of the curve accurately. Despite the additional uncertainty, this method of estimating the demand curve and formalization of willingness-to-pay is generally accepted as a better measure of the benefits of electrification. In Figure 15.7, the demand curve is shown typically concave (with respect to the origin). This shape frequently emerges where more than two points on the curve can be plotted. A concave shape also follows from the (convenient) assumption of constant elasticity (often made in econometric models). Before electrification, these services are usually provided by a mix of kerosene (for lighting) and batteries (for TVs and radios). For simplicity, assume that the only service provided is lighting from kerosene lamps. Then the quantity of services consumed is Qkero, at the market price pkero. Thus, the total lighting cost to the household is (Qkero × pkero), equal to the area (B + B*+ D + D*]. The total willingness-to-pay for the service at level Qkero is the total area under the demand curve up to that level of consumption, or area (A + B + B* + D + D*]. This is the total benefit to the consumer. Therefore, the net benefit (benefit minus cost), also called the consumer surplus, is given by area A. After electrification, the level of service (for lighting – the number of lumen-hours) typically rises sharply. Thus, consumption increases from Qkero to QE, but the price paid for electrified service also falls from Pkero to PE. Now household expenditure for electricity is given by (pE × QE), equal to area (D + D* + E + E*). At this level of consumption, the total benefit is the new area under the demand curve up to QE, (A + B + B* + C + D + D* + E + E*). Then the net benefit, or consumer surplus (after subtracting costs), is given by (A + B + B* + C). Thus, the net economic benefit (with versus without electrification) is the increase in consumer surplus, which is the area (B + B* + C). Areas (B + B*), (D + D*) and (E + E*) are readily calculated from data on consumption with and without electrification, the household budget for kerosene (and battery charging) and the tariff of electrified service. But area C is more difficult to estimate, since it requires knowledge of the shape of the demand curve. A linear demand curve is the most convenient and frequently used one (ECA and Vernstrom, 2003). Unfortunately such an assumption may lead to an overestimation of area C (and net benefits of electrification), since empirically the demand curve is more likely to have a concave shape. Given some functional form for such a demand curve, area C is readily calculated as the definite integral. Consumer surplus calculations use financial costs (since these are the costs actually seen by the user). However, financial and economic costs need careful estimation and reconciliation, because often the quantities both with and without electrification are subject to taxes and subsidies. Figure 15.7 shows a typical situation where the price of kerosene includes taxes (i.e. market price pkero exceeds economic price pKE) and

522


Table 15.6 Reconciliation of economic and financial flows Kerosene Consumer surplus Taxes and duties (VAT) Subsidy Economic cost Total benefit to consumer (= area under demand curve)

Electrification

A B*

A + B* + B + C D* + E* −SQE B + D* + D D + E + SQE A + B* +B + D* +D A + B + B* + C + D * D + E* + E

Difference B + B* + C D* + E* − B* −SQE E + SQE − B − D* C + E* + E

where electrification involves both taxes (like VAT on construction costs) and subsidies (provided by government). Suppose the electrification subsidy is Rs S/kWh. Then we may write pES = pEE − S, where pEE and pES are the economic and subsidized prices, respectively. Thus, the total amount of the subsidy is the area SQE. Suppose that this subsidized price is also taxed at the rate Rs T/kWh. Then, the market price to the consumer increases to pE = pES + T (the amount of taxes collected being the area D* + E*). In Figure 15.7, the subsidy exceeds the tax – which is the case for microhydro systems in Sri Lanka, where the proposed subsidy far exceeds the amount of VAT and profits tax on construction. For kerosene, the total (financial) cost to the user is given by (B* + B + D* + D). Of this total, area B* represents taxes. Table 15.6 reconciles various economic and financial quantities. For example, without electrification, the economic benefit is (A + B*), but area B* is captured by government as tax, rather than benefiting the consumer.

15.4.2 Solar homes programme in Sri Lanka Solar home systems (SHSs) are designed to provide the most high-valued, initial tranche of electricity consumption, in rural areas in Sri Lanka, that are unlikely to be grid-connected soon. Nevertheless, according to Shell Solar, the leading supplier of SHSs, 10 000 of 17 000 systems sold to date have been to households where the grid was extended after the SHS had been installed. Indeed, there are also reports of households already connected to the grid buying an SHS. Evidently the erratic nature of rural supply (due to power cuts) and CEB’s high consumer tariff are powerful incentives for SHS purchases. The ESD project, supported by the World Bank and GEF, has helped finance SHSs. The solar industry was at a nascent stage when the ESD project became effective, with only three small operators (Solar Power and Light, Sarvodaya and RESCO) selling 20–30 systems per month in 1998. The ESD project has catalysed the market for SHSs. By 2002, sales had reached 850 systems per month, achieved by four companies (Shell Solar, Access Solar, SELCO and Alpha Thermal); 21 000 systems were installed, and 2003 sales exceeded 10 000 systems.


523

The very success of the ESD project in stimulating a successful private-sector involvement poses difficulties for economic analysis, because much of the data on actual system costs and margins are confidential. In addition, tax concessions vary by company. However, both strong consumer and vendor interest in this market are testimony to the economic benefits of SHSs (given the demonstrated willingness-to-pay for lighting and TV service at a cost well above the cost of kerosene and battery charging) and to the financial benefits (given the financial success of the vendors). Several surveys provide information on monthly expenditures of households that purchased SHSs (see Table 15.7). Although the results show considerable variation, the data do indicate a substantial willingness-to-pay for the safety, convenience and superior light quality from an SHS. Before SHSs, monthly average energy expenses totalled Rs 582 (Rs 340 for kerosene, Rs 92 for dry cells and Rs 152 for battery charging). However, there was little correlation between energy expenses and disposable income. Monthly energy expenses increased sharply upon purchase of the SHS (see Figure 15.8). Households did recognize that these higher costs would be limited to the debt-repayment period, and that thereafter their energy expenditures would decrease sharply. The average monthly energy expenditure of SHS

Table 15.7 Survey results before and after SHS purchase Masse (2001) IRG (2002) AC Nielsen (2003) Monthly kerosene expenses (Rs) 231 Total monthly energy expenses before SHS 321 Average monthly energy expenses after SHS – Sample size –

340 582 1450 100

312 495 1286 250

40

number of households

kerosene + batteries 30

20

SHS

10

0 200 600 1000 1400 1800 2200 2600 3000 3400 3800 4200 monthly expenditure (Rs 1000)

Figure 15.8. Monthly energy expenditures before and after SHS.

524


households was Rs 1450. There was little correlation between income and the size of the SHS purchased. If one calculates the benefits on the basis of avoided costs, the economic returns of an SHS are negative. The AC Nielsen survey (AC Nielsen, 2003) shows: (1) mean monthly expenditure on kerosene and battery charging before the SHS is Rs 495/month; (2) four-year loan at 24% interest, with 25% down-payment; (3) 12% discount rate; (4) VAT on SHS is 11% of retail price; (5) kerosene tax limited to National Security Levy (Rs1.23/litre); and (6) SHS retail price is Rs 46 000 (45 watts-peak (WP) system). Table 15.8 shows a 7.7% internal economic rate of return (IERR), less than the opportunity cost of capital (OCC = 12%), while the financial rate of return to homes is negative. This result is consistent with other estimates, where avoided costs are used to measure benefits. For example, Meier (2003) found that the IERR of a 40 WP SHS in the Philippines was 11.7% (below the OCC = 15%). Table 15.9 reconciles economic and financial flows among stakeholders. Because the financial interest rate is 24%, whereas the discount rate is 12%, the difference appears as a residual benefit to financial institutions (FIs). GEF is a source of funds, and thus shows up as a financier, while the government is a net beneficiary, since the VAT levied on the SHS (paid by the dealers) significantly exceeds any VAT on kerosene lamps and battery charging and the National Security Levy on kerosene. The apparent negative financial return to homes reflects the highly negative cash flows in early years, when the loan is paid off (see Figure 15.9). Therefore, the returns must be higher than those assessed purely on the basis of the replacement costs – since consumers are in fact willing to pay the higher outlays for SHS. Using the approach outlined earlier, we may derive the demand curve for lighting shown in Figure 15.10, for a homeowner purchasing a 45 WP system. The corresponding distribution of costs and benefits is summarized in Figure 15.11, based on the consumer surplus calculations shown in Table 15.10. The IERR is a robust 31%, which increases to 42.6% when the GEF contribution is added as an environmental benefit. A 75 WP system generates about 315 Wh/day, or 115 kWh/yr, whose NPV over 15 years is 700 kWh. The NPVof the financial costs of the PV system is Rs 63 054. Hence, the implied willingness-to-pay for the first 115 kWh/yr provided by SHS (for lighting and TV viewing) is 63 054/700 = Rs 90/kWh (about US $1/kWh). To conclude, it seems reasonable to claim that SHS represents a viable approach to offgrid electrification, and that subsidies from GEF are cost-effective for levering economic benefits not otherwise achievable because of financing problems. Moreover, the demonstrated willingness-to-pay for SHS (above replacement costs) shows the value of estimating consumer surplus, rather than using replacement costs, which underestimate benefits.

15.4.3 Village hydro Small microhydro systems were a second successful part of the ESD project in Sri Lanka. They are under 50 kW and implemented by village cooperatives. AC Nielsen (2003) surveyed 100 village hydro system (VHS) beneficiaries and 30 of the VHSs implemented

14 570 −1457 13 113 39 948 1314 32118

Economic O&M costs (Rs)

Total economic costs (Rs)

Benefits at avoided costs Kerosene consumption (l) Kerosene (Rs)

3539 2465 8566

26 835

Financial cost to consumer (Rs) Less VAT (Rs)

O&M costs Bulbs (Rs) Controller (Rs) Battery (Rs)

Economic capital cost (Rs)

38 217 −38 217 −4107 −5252 −4877

41071

Financial cost (Rs)

Finance (Rs) Loan repayments (Rs) Less VAT & duties (Rs) Less income tax on margin (Rs) Less transfers (Rs)

10 268 0 0 30 804

Costs of PV system Down payment (Rs) GEF to consumer (Rs) Govt. grant (to consumer) (Rs) Loan principal (Rs)

NPV

1

30 055

0

0 0

30 055

−4600 −5882 −5462

46000

11 500 0 0 34 500

216 5282

524

524

582 −58

582

0

16 905 −16 905

2

Table 15.8 Economic and financial returns based on avoided costs

216 5282

524

524

582 −58

582

0

14 835 −14 835

3

216 5282

4802

4802

5335 −534

4753

582

0

12 765 −12 765

4

216 5282

524

524

582 −58

582

0

10 695 −10 695

5

0

216 5282

3317

3317

3686 −369

582 3104

6

582

216 5282

4802

4802

5335 −534

4753

7

524

524

582 −58

582

216 5282

8

−4126

Net economic flows (Rs) ERR

−26 930

0

0

0 0

−11 500 −4.5%

11 500 0

−30 055 7.7%

1

ERR = economic rate of return; FRR = financial rate of return.

Net flow (Rs) FRR

63 054 36 124

35 822

Avoided costs (Rs)

Net financial impact on consumers PV system (Rs) Replacement (Rs)

37 437 −1616 0

4006 0 0 0 0

NPV

Total, financial (Rs) Kerosene duties (Rs) VAT (Rs)

Battery & charging (Rs) Dry cell (Rs) Hurricane lamp (Rs) Petromax lamp (Rs) Wick, gauzes (Rs)

Table 15.8 (cont.)

17 487 5940

5151

5675

5940 −266

0

659 0

−11 547

2

3

−9477

15 417 5940

5151

5675

5940 −266

0

659 0

18 100 5940

873

5675

5940 −266

0

659 0 0

−12 160

4

5

−5337

11 277 5940

5151

5675

5940 −266

0 0

659 0

0

659 0

2254

3686 5940

2357

5675

5940 −266

6

0

659 0 0

605

5335 5940

873

5675

5940 −266

7

0

659 0

5358

582 5940

5151

5675

5940 −266

8


527

Table 15.9 Reconciliation of economic and financial flows (as NPV) Consumer Benefits Purchase price Loan GEF grant Govt grant VAT (on equipment) Income tax (dealers) Income tax (FIs) Economic cost Consumer finance O&M costs Total

37 437 −41 071 30 804

Dealers

Govt

FIs

GEF

−1616 41 071 −30 804 −6790

6 790 −4107 −5252

4107 5252 2595

−2595

−26 835 −38 217 −14 570 −25 617

38 217 11 667

1457 11 795

4819

−6790

Total 35 822 0 0 0 0 0 0 0 −26 835 0 −13 113 −4126

10

(Rs 1000)

5

0

–5

–10

–15

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 year

Figure 15.9. Cash flows to homeowners, in Rs/yr.

under ESD. Unfortunately, inadequate data from the village cooperatives make it difficult to determine precisely some key parameters, such as actual monthly and annual capacity factors. At the time of appraisal, the IERR was estimated at 12%, which has the appearance of being contrived for the sake of meeting the OCC = 12% hurdle rate. However, evaluation of systems actually implemented reveals lower costs, and thus greater economic benefits than expected. For example, while the estimated cost is US $2023/kW, the completed projects reported by the survey show an average capital cost of US $1892/kW. Figure 15.12 shows how unit capital cost varies against installed capacity, and confirms the strong presence of scale economies. Further, there is a large ‘sweat equity’ component

528

Project and local applications 0.012

(Rs/ lumen h)

0.01 0.008

B = 979

C = 296

D = 4303

E = 2955

0.006 0.004 0.002 0 0

200

400 600 1000 lumen-hours / yr

800

1000

Figure 15.10. Demand curve for lighting (based on 45 WP PV system).

40 37

NPV (Rs 1000)

30

20 TV/radio 7.8

10

11.7

11.8

lighting 7.7 4.8

0 –6.8

–10

consumers

govt dealers

GEF FIs

total

Figure 15.11. Distribution of costs and benefits.

based on voluntary labour. Using an average income of Rs 300/day, the survey report estimates the ‘minimum opportunity cost of voluntary service rendered by the average VHS user at Rs 9000 (30 man-days)’. The beneficiary survey reveals that 20–30 days is the most frequent contribution of voluntary service. Table 15.11 shows sweat equity costs, using the opportunity cost of contributed time (based on home income). Taking the cash equity fraction at 15%, and conservatively assuming that 25% of project cost are imports, then economic capital costs (including sweat equity) are US $2060/kW, and financial capital costs are US $2225/kW (excluding sweat equity). Records of kilowatt-hours actually produced are sparse. Indeed, actual readings were available for only seven systems (column [3] of Table 15.12). The period of operation could

32 118 3 315 928 0.0097 5282 30% 18 916 18 916 11 098 1.7 3111 4006 1665 2.4 659

Radio/TV: PV system [15] Allocated costs [16] PV costs, financial (Rs) [17] PV costs, levelized (Rs) [18] PV non-lighting (VL-h) [19] PPV (Rs/TV-h) [20] Area (D +E) (Rs/yr)

Radio/TV: battery [21] Total costs (Rs) [22] PV non-lighting (VL-h) [23] Pbattery (Rs/TV-h) [24] Area (B + D) (Rs/yr)

70% 44 138 44 138 5 593 422 0.0079 7258

[11] Total costs (Rs) [12] Kerosene lighting (lumen) [13] Pkero (Rs/litre) [14] Area (B + D) (Rs/yr)

Lighting costs, kerosene [7] Fuel cost (Rs) [8] Wick lamp (Rs) [9] Petromax lamp (Rs) [10] Wick, gauzes (Rs)

Lighting costs, PV system [1] Allocated costs [2] PV costs, financial (Rs) [3] PV costs, levelized (Rs) [4] PV lighting (lumen) [5] PPV (Rs/lumen h) [6] Area (D + E) (Rs/yr)

NPV

1

0

3450 2712

0

0 0 0

8050 6329 0

659 274

5246 2712 1825

5282 545 282

5282 0 0 0

12 241 6329 919 800

2

Table 15.10 IERR with consumer surplus benefits (15 year life of SHS)

659 274

4625 2712 1825

5282 545 282

5282 0 0 0

10 792 6329 919 800

3

659 274

5430 2712 1825

5282 545 282

5282 0 0 0

12 670 6329 919 800

4

659 274

3383 2712 1825

5282 545 282

5282 0 0 0

7894 6329 919 800

5

659 274

1106 2712 1825

5282 545 282

5282 0 0 0

2580 6329 919 800

6

659 274

1601 2712 1825

5282 545 282

5282 0 0 0

3735 6329 919 800

7

659 274

175 2712 1825

5282 545 282

5282 0 0 0

407 6329 919 800

8

11 795 −6790 4819 11667 37 032

[39] Less net govt subsidies (Rs/yr) [40] Less GEF subsidies (Rs/yr) [41] Plus FI surplus (Rs/yr) [42] Plus dealer surplus (Rs/yr)

[43] Net economic flows (Rs/yr) [44] ERR [45] With GEF as economic benefit (Rs/yr) [46] ERR

−17 485 31.0% −9881 42.6%

1920 1920

−150

4413 1920

−150

4413 −150

1970

−233

4392 4625

2203

8532 6329

−15 417 12 924 −2493

3

1165

−1038

4392 5430

2203

8532 6329

−763

−763

4413 −763

−18 100 12 924 −5176

4

3212

1009

4392 3383

2203

8532 6329

6060

6060

4413 6060

−11 277 12 924 1647

5

6

13 651

13 651

4413 13 651

−3686 12 924 9238

5490

3286

4392 1106

2203

8532 6329

7

12 002

12 002

4413 12 002

−5335 12 924 7589

4995

2792

4392 1601

2203

8532 6329

8

16 755

16 755

4413 16 755

−582 12 924 12 342

6421

4217

4392 175

2203

8532 6329

Without the ‘economic cost adjustment’ of rows [36]–[38], the economic flows have more than one turning point (since subsidies and adjustments occur in year 1). Then IERR is indeterminate. NPV calculations are unaffected. The adjustment for taking the GEF contribution as a benefit in year 1 assumes that it is equal to global environmental benefits. Areas B, C, D and E refer to Figure 15.10.

43 822

−30 055 −41 555 16.8%

−0 15 541

[36] Economic cost adjustment (Rs/yr) [37] Adjusted net financial flow (Rs/yr) [38] ERR 13 211 −7605 5397 13067

−11 500 0 −11 500 21.1%

−63 054 78 595 15 541

[32] Total financial costs (Rs/yr) [33] Total consumer surplus benefits (Rs/yr) [34] Net financial flows (Rs/yr) [35] ERR

−17 487 12 924 −4563

1349

−9779 30.7%

15541

Total consumer surplus (Rs/yr) [31] ERR

−854

7792

[30] Net consumer benefits, TV/radio (Rs/yr)

2203

−6329

−3450

26 708 18 916

TV/radio [28] Total benefits (B + C + D + E) (Rs/yr) [29] Total costs (D + E) (Rs/yr)

8532 6329

0 6329

2

4392 5246

7749

[27] Net consumer benefits, lighting (Rs/yr)

1

3450

51 887 44 138

NPV

Net economic flows Lighting (see chart) [25] Total benefits (B + C + D + E) (Rs/yr) [26] Total costs (D + E) (Rs/yr)

Table 15.10 (cont.)


531

Table 15.11 Estimates of sweat equity Sweat Cash Total village Project Sweat equity equity equity cost equity (%) System

[1]

Handunella 0 Aluthgama 561 Diyapoda 280 Manamperigama 168 Dumbara 1527 Average

Cash Adjusted cash equity (%) equity (%)

[2]

[3]

[4]

[5] = [1]/[4] [6] = [2]/[4] [7] = [2]/([4]−[1])

125 102 134 24 470

125 603 414 912 1997

1325 1307 1152 800 3700

0 43 24 21 41 26

9 8 12 3 13 9

9 14 15 4 22 13

3500

capital cost ($1000/kW)

3000 2500 2000 1500 1000 500

0

5

10 15 installed capacity (kW)

20

25

Figure 15.12. Capital cost versus installed capacity.

be inferred from knowledge of commissioning dates to derive average annual kilowatt-hours, and hence estimate the average capacity factor, with the results as shown in column [5]. Overall, it seems reasonable to infer that the achieved capacity factors are in the range of 80–95%. These capacity factors are much higher than the 50% estimated at appraisal. However, they are consistent with the design philosophy, which matches system size to dry season flows. Clearly, if a village hydro system were only operated at a 50% capacity factor, then diesel backup would be needed to supply year-round power. Although VHSs were built in small watersheds and generally well above gauging stations, none maintained records of gauged flows at the intake. Therefore, the likely monthly variation in flows can only be inferred from precipitation records that are generally available. Figure 15.13 shows the monthly variation in rainfall at the Ingoya Estate, on which the design flow for the Handunella–Atulauda VHS is based. If one matches the design flow to January/February conditions, high annual capacity factors are achievable. However, on a daily load curve basis, it seems unlikely that this

532


Table 15.12 Capacity factor estimates

Maddabaddara Kandaloya Handunella Gedarawat Golahinna Kaduoya Kawudubukka Veediyawa Samanala Ihalagonna Glime Hathkella Hinguralakande Gamperigama Dumbara-Manana Wewagama Ritigala Ella

Estimated annual kWh survey

Estimated capacity factor survey

Actual meter reading (Spring 2003)

Months

Estimated capacity factor (meter reading)

[1]

[2]

[3]

[4]

[5]

35 040 74 256 113 568 76 752 162 060 109 200 131 400 51 480 148 512 60 840 33 670 87 360 65 700 4269 24 768 32 850 131 400

0.889 0.848 0.997 0.73 1 0.831 1 0.131 0.997 0.926 0.769 0.997 1 0.139 0.133 1 1

352 716 321 776

56 34

0.863 1.012

327 600

37

0.809

179 406

24

0.232

91 260 73 002

18 21

0.926 0.976

2490

7

0.139

average monthly rainfall (mm)

800

600

400

200

ne Ju ly A ug Se pt O ct N ov D ec

ay

Ju

M

b

ar pr A

M

Fe

Ja

n

0

Figure 15.13. Monthly rainfall patterns for Ingoya Estate.

continuously available power is actually consumed, given the probable end uses of lighting and TV. The VHS beneficiaries have average monthly costs (on kerosene, batteries and dry cells) of Rs 322/month. Taking this as the benefits (plus the GEF grant), and using the actually


533

Table 15.13 Achieved IERR NPV

[0]

[1]

[2]

[3]

[4]

[5]

[6]

Capital cost = US $2050/kW Kilowatts = 15.0 GEF grant ($US) 4783 6000 Capital costs ($US) −27 455 −30 750 O&M costs 0.8% ($US) −1702 −6255 −255 −255 −255 −255 −255 Total costs ($US) −24 374 −30 750 5745 −255 −255 −255 −255 −255 Capacity factor = 0.8 Benefit/kWh = 5.7 US cents/kWh Benefits (MWh) 105 105 105 105 105 105 ($US) 39 960 5992 5992 5992 5992 5992 5992 Total flows ($US) 15 586 −30 750 11737 5737 5737 5737 5737 5737 IERR 21.8%

frequency

6

4

2

0

0.03

0.09

0.15 0.21 0.27 0.33 0.39 economic rate of return, ERR

0.45

Figure 15.14. IERRs for surveyed VHS.

achieved capital cost of US $2050/kW, the IERR is 21.8% for the same VHS (15 kW, 150 households) used at appraisal. Without the GEF grant benefit, the IERR is 17.9%. Whether or not high levels of electricity are actually used does not affect this result, since benefits are taken as pre-electrification energy expenses. If smaller amounts of electricity were used, then the average benefit US $0.057/kWh would be that much greater. Based on the survey results, we may estimate the IERRs achieved for individual VHS systems as shown in Figure 15.14. These estimates of IERR (based on replacement costs) significantly underestimate actual economic returns, because willingness-to-pay for the first tranche of electricity use is much greater than replacement costs. In Section 15.4.2, we showed that this first tranche (115 kWh/yr) may be valued at US $1/kWh (VHS and SHS customers have similar income

534


Table 15.14 Benefits based on consumer surplus NPV Capital cost = US $2050/kW Kilowatts = 15.0 GEF grant ($ US) 4783 Capital costs ($ US) −27 455 Lost earnings (sweat equity) −690 ($ US) O&M costs 0.8% ($ US) −1702 Total costs ($ US) Capacity factor = 0.8 Benefit/kWh = 20.2 US cents/kWh Benefits (MWh) ($ US) Total flows ($ US)

[0]

[1]

[2]

[5]

[6]

−773

−25 065 −31 523

115 043 89 978 −31 523

767 115 043

[4]

6000 −30 750

−255

−255

−255

−255

−255

−255

5745

−255

−255

−255

−255

−255

30 30 30 30 30 30 17 250 17 250 17 250 17 250 17 250 17 250 22 995 16 995 16 995 16 995 16 995 16 995

Estimate of benefits based on willingness-to-pay TP Consumption = 6h/day Number of households (HH) = 150 90 W/HH Wh/day/HH 3601 540 kWh/yr/HH 1314 197 First tranche 1 US $/kWh 115 kWh 767 115 US $/yr/HH 767 115 Second tranche kWh 548 82.1 0 US $/kWh US $/yr/HH 0 0 Total WTP US $/yr/HH US $/yr

[3]

115 17 250

540 197

540 197

540 197

540 197

540 197

115 115 82.1

115 115 82.1

115 115 82.1

115 115 82.1

115 115 82.1

0

0

0

0

0

115 115 115 115 115 17 250 17 250 17 250 17 250 17 250

levels). Assuming further that actual use is limited to evening TV viewing and lighting, and that each household has 100 W of installed devices that run for 6 h/day on average, then total annual consumption is given by 6 × 100 × 0.9 × 365/1000 = 197 kWh/yr, implying a second tranche of 82 kWh/yr. Then, even the willingness-to-pay is zero for this second tranche, and the computed IERR is 61%, as shown by the calculations of Table 15.14 (54% without the GEF grant). Table 15.15 shows the distribution of costs and benefits. The bulk of the economic benefit accrues to the consumer, with some portion accruing to village cooperatives – though, in


535

Table 15.15 Distribution of costs (−) and benefits (+) in US dollars

Item

Consumers Govt

Electricity 115 043 Environmental Fees −39 974 Lost earnings −690 Grants Capital costs O&M costs NSL, kerosene 2216 Taxes and duties on capital cost Total 76 594

VHS

GEF

Total

Global Total (including environment environment)

115 043 0 4783 39 974 0 −690 0 −4783 0 −27 455 −27 455 −1702 −1702 −2216 0 2344 −2344 0 128

8 472

85 195

115 043 4783 0 −690 −4783 −27 455 −1702 0 0 89 978

practice, some of this surplus is likely to be passed back to the consumer beneficiaries (because of non-payment of dues, refunds of cash surpluses, etc). The GEF grant is shown as a subsidy, assumed to be equal to the global environmental benefit. For government, the loss of National Security Levy (on kerosene) is roughly offset by taxes and duties on capital costs. Box 15.2 shows contrasting results from the Philippines, where diesel plant is cheaper than small hydro. Further, IERR calculations may be uncertain, and are better viewed as probability distributions, rather than single deterministic numbers. In Box 15.3, Monte Carlo simulations are applied to estimate the likely probability distributions of ex-ante rates of return on projects in Vietnam. In summary, the achieved economic benefits are substantially greater than those estimated at appraisal. First, capacity factors are significantly greater, as a consequence of the design approach followed by consulting firms and developers – where systems are sized on the basis of the available average dry season flow. Second, actual capital costs are slightly lower than estimated. Finally, expenses for kerosene and battery prior to electric service have increased significantly since 1996, due to real income gains. Thus the willingness-to-pay for electric service is higher. Thus, from an economic viewpoint, village hydro systems bring large benefits and should continue to be promoted for off-grid electrification in areas where the grid access is not possible in the short to medium term.

15.5 Evaluating a typical water supply project in a poor African village In this section, a simple rural water supply project in a poor African village is analysed (Munasinghe, 1977, 1992b). The focus is on the quantitative study of economic aspects, using CBA (see Chapter 3). Our procedure includes the demand forecast, the least-cost investment programme, the IERR, the incremental cost of supply and price. The emphasis is

536


Box 15.2 Philippines – analysis of isolated mini-grids Hydro is not always as economic as in Sri Lanka for isolated mini-grids. In the Philippines, diesel plants were least-cost when compared with small hydro alternatives. Table B15.1 summarizes some key results of feasibility studies for six communities on two islands, where grid extension was not economic. Table B15.1 Comparison of diesel and small hydro costs in the Philippines

First-year number connected homes Roxas El Nido SanVicente Taytay Palawan Jose Abas Santos Malita Davao

1441 479 413 1216 3549 796 1778 2575

First-year installed capacity (kW) 625 250 185 575 1625 310 685 990

IERR, diesel (%) 32.6 11.2 19.7 25.6 28.2 8.9 25.1 20.6

Levelized costs (US cents/kWh) diesel 15 19.1 18.1 16.1 15.3 21.6 16.3 17.6

hydro 26 54 39

23 41

Boldface = economically viable (IERR > 15% hurdle rate).

The average willingness-to-pay in the Philippines was estimated for a typical household consumption tranche of 300 kWh/yr at US $0.3/kWh. Figure B15.1 shows the demand curve for the Philippines, derived from empirically established marginal willingness-topay for different types of systems. willingness-to-pay (US $ / kWh)

2.5 2

20 WP SHS

1.5 1

40 WP SHS 75 WP SHS

0.5

mini-grid 0

0

100

200 kWh / yr

300

400

Figure B15.1. Willingness-to-pay versus annual electricity use in the Philippines.

The highest willingness-to-pay is for the first tranche of about 30 kWh/month, as is typically provided by 20 WP solar home systems, but thereafter the willingness-to-pay falls sharply to a typical US $0.15/kWh tariff charged in a Philippines mini-grid – which is a level confirmed by the observed willingness-to-pay for TV viewing of nonelectrified households (by battery charging).


537

Box 15.3 Vietnam: probability distribution of the rate of return Simple calculations of an economic rate of return may suffice for an ex-post analysis to evaluate whether a project has met its original objectives. However, for an ex-ante analysis during project appraisal (when data are less certain, and there may be a number of project alternatives), more sophisticated approaches are required. One common technique is Monte Carlo simulation, where each key input assumption is specified as a probability distribution (rather than one ‘best’ value). The IERR calculation is then repeated a large number of times (typically 1000 to 10 000), drawing at each calculation some sample value for each of the input assumptions. In this way a probability distribution of IERR is generated. Figure B15.2 exemplifies the approach, based on the analysis of small hydro-projects in Vietnam to serve isolated communes not presently connected to the grid. Probability distributions for each alternative (hydro, grid extension and diesel plants) are shown – each of which is subject to its own set of uncertainties. This allows not only an assessment of the expected value of IERR, but also the trade-off with risk, which we can express as the probability that the hurdle rate is not achieved (i.e. area under the curve to the left of the 10% hurdle rate). 0.6

prob (ERR < 10%) diesel = 16% hydro = 10% grid = 99% grid

hydro

probability

0.4 diesel 0.2

0 0.025 0.075 0.125 0.175 0.225 0.275 0.325 0.375 0.425 0.475 economic rate of return, ERR

Figure B15.2. Probability distribution of the economic rate of return for small hydro-

projects in Vietnam. The comparison of expected returns and risks for four communes is shown in Tables B15.2 and B15.3. The clearly expected value alone does not tell the full story. For example, in the case of Phu Nam and Giap Trung, all three alternatives have comparable expected values, but hydro has significantly lower risk, and so the hydro option would be preferred. In the case of Bat Mot, diesel has both the highest expected return (and lowest risk). For Giap Trung, grid extension is indicated (since neither hydro nor diesel has a clear advantage), though the diesel option has the highest risk.

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Table B15.2 Internal economic rate of return (IERR)

Hydro (%) Grid extension (%) Diesel (%)

Bat Mot

Giap Trung

Thong Thu

Phu Nam

11.9 12.1 16.1

13.4 14.7 12.8

14.3 7.3 18.4

15.0 14.4 15.7

Table B15.3 Risk of IERR < hurdle rate of 10%

Hydro (%) Grid extension (%) Diesel (%)

Bat Mot

Giap Trung

Thong Thu

Phu Nam

27 20 18

4 8 26

11 98 18

14 20 28

This example shows not only that a probability distribution of IERR is better than a single point (deterministic) estimate, but also that trade-offs between expected return and risk are often required. on how demand, costs and revenue data may be used for effective decision making. The evaluation also takes environmental and social considerations into account, but in a qualitative manner.

15.5.1 Water-demand forecast The demand forecast for the township area encompassed by the project is shown in Table 15.16 (see Section 14.7 for details about demand projections). In the second and third columns, total population and total demand give an indication of overall system size. The incremental demand refers to water which must be supplied via new investments, inclusive of sources required to replace existing ones that are expected to go out of service in the future. Thus, the increase in total demand from year 1 to year 2 is only 413 m3/day (i.e. 4548–4135 m3/day), but the total incremental demand met (from new investments) is 700 m3/day, because of existing sources that have to be replaced. By year 11, the total demand and total incremental demand met are identical (8763 m3/day), since all existing sources would have gone out of service. Incremental demand is the key variable for this calculation – domestic consumers are the most important, followed by government and, finally, industrial users. The percentage of water unaccounted for (or fraction of water produced which is not used) decreases steadily due to improvements to the system, better billing, etc. Total incremental supply is equal to the sum of total demand and unaccounted for water. We note that incremental demand (and supply) begin in year 2, only after corresponding investments which had started in year 0 (Table 15.17) have become operational. The 20-year time


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Table 15.16 Demand forecast

Year

Total Total population demand (1000) (m3/day)

0 (now) 121.5 3717 1 125.7 4135 2 130.1 4548 3 134.6 4983 4 139.4 5416 5 144.2 5904 6 149 6350 7 153.9 6796 8 158.9 7250 9 164.2 7647 10 169.7 8134 11 175.3 8763 12 180.9 9328 13 187 9892 14 193.1 10 600 15 199.6 11 300 16 207 12 000 17 no additional demand 18 is considered beyond 19 this period since it 20 will not be serviced by sources included in this analysis

Incremental demand met by new sources Water (m3/day) unaccounted Household Government Industrial Total for (%)

Total incremental supply (m3/day)

0 0 420 900 1356 1860 2328 2760 3030 3476 4035 5258 5597 5935 6360 6780 7200 6667 6173 5716 5292

0 0 875 1875 2825 3875 4790 5679 6235 7152 8200 10 687 11 376 12 063 12 927 13 780 14 634 13 550 12 546 11 617 10 756

0 0 210 450 678 930 1164 1380 1515 1737 2017 2629 2798 2968 3180 3390 3600 3333 3086 2858 2646

0 0 70 150 226 310 388 460 505 579 672 876 933 989 1060 1130 1200 1111 1029 952 882

0 0 700 1500 2260 3100 3880 4600 5050 5793 6724 8763 9328 9892 10 600 11 300 12 000 11 111 10 288 9526 8820

20 20 20 20 20 20 19 19 19 19 18 18 18 18 18 18 18 18 18 18 18

horizon is sufficient to ensure that due to the cumulative effects of discounting, events occurring beyond this period have negligible impact on the results. In fact, by year 16 all facilities are operating at full capacity. Thereafter, no new sources are considered, and the incremental demand met by existing sources declines steadily due to wear and tear.

15.5.2 Least-cost investment programme For illustrative purposes, we assume that the two best feasible alternative system expansion programmes or sequences for meeting the demand, are: (1) a reservoir followed by a series of boreholes; or (2) a borehole followed by a reservoir and more boreholes.

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Table 15.17 Supply costs for alternative 1 Investment costs (103L)a Local constructionc Year Direct importsb DP

BP

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

170 113.1

300 200

200 133

30 75

20 25

17 21.3

120

40

34

150

50

42.5

30

20

17

O & M costs (103L)a

Direct importsb

Local investment Local goodsd Electricitye labour f

Total costs (103L)

DP BP

DP BP

DP BP

BP

0 0 6 14 20 32 44 56 60 88 92 97 103 110 115 119 110 102 94 87 80

0 0 3 7 10 20 32 48 56 85 96 106 114 125 136 145 134 124 113 105 97

0 0 2 4 6 14 28 42 50 81 95 106 114 125 136 145 134 124 113 105 97

0 0 10 25 35 60 90 110 150 195 250 275 300 315 340 360 335 316 280 260 240

470 313.1 18.8 45 63.6 112.2 171.7 226.3 324.9 491.4 466.9 665 551.8 782.8 635.2 671.5 622.6 581.4 524.1 486.5 448.9

2.7 6.3 9 18 28.8 43.2 50.4 76.5 86.4 95.4 102.6 112.5 122.4 130.5 120.6 111.6 101.7 94.5 87.3

1.6 3.2 4.8 11.2 22.4 33.6 40 64.8 76 84.8 91.2 100 108.8 116 107.2 99.2 90.4 84 77.6

8.5 21.5 29.8 51 76.5 93.5 127.5 165.8 212.5 233.8 255 267.8 289 306 284.8 268.6 238 221 204

DP = domestic price; BP = border price. a All costs in real 1990 local currency units (L); official exchange rate US $1 = L1. b Net of duties and taxes, already in border prices. c Construction conversion factor = 0.85 for general inputs from the local construction sector (including labour). d Investment conversion factor = 0.9 for aggregate of locally purchased investment items. e Electricity conversion factor = 0.8 for electricity input; ideally, the border price should reflect the long-run marginal cost of supply of electricity. f Labour conversion factor or shadow wage rate (SWR) = 0.85. This is a weighted average of unskilled SWR = 0.55 and skilled SWR = 0.95.


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There are ample supplies of both groundwater and surface water available, so that cost complications due to depletion effects (e.g. lowering of the water table and increased pumping costs) do not arise – externalities due to groundwater depletion are described in Chapter 12. We wish to identify the least-cost alternative (i.e. the one with the lowest present value of costs) – see Section 3.2.1. In this study (and most cases) there could be more than two alternatives. However, we compare only two different expansion options to illustrate the methodology. The same principles may be used to compare more than two alternatives. The typical cost breakdown associated with the first alternative is given in Table 15.17. The second alternative (not shown here) has a somewhat different profile of costs. Certain costs that are common to both alternatives (e.g. distribution, operation and maintenance and connection costs) may be netted out without affecting the results of the least-cost analysis. However, these costs have been included in the tables because they will be required for the rate of return and marginal cost estimation to follow. The shadow-pricing procedure described in Chapter 3 is used. All costs are in local currency units (L), in real 1990 prices. The reference official exchange rate is US $1 = L1. The two columns in Table 15.17 marked ‘Direct imports’ are net of duties and taxes and are converted directly into border prices (using the official exchange rate). Local construction sector inputs are converted from domestic to border prices using the construction conversion factor of 0.85. Similarly, an investment conversion factor of 0.9 applies to locally purchased goods used in operation and maintenance. Domestic-priced electricity inputs are converted to border prices using the electricity conversion factor of 0.8. Thus, border-priced electricity is adjusted to reflect the long-run marginal cost (LRMC) of power supply (see Chapter 14). Finally, a shadow wage rate (SWR) or labour conversion factor of 0.85 is used to border price local labour inputs. This aggregate SWR is a weighted average of 75% skilled labour (with SSWR = 0.95) and 25% unskilled labour (USWR = 0.55). Finally, all columns involving direct imports and border-priced costs are added together in the final column to yield the total costs of alternative 1 in border prices. Exactly the same procedure is followed to analyse the costs of the second alternative. The present values of cost streams for both alternatives are given in Table 15.18, for several different discount rates. Clearly, alternative 1 is better than alternative 2 for discount rates ranging from 0 to over 20% (i.e. alternative 1 has a lower present value of costs). The opportunity cost of capital for this specific example falls in the range 10% to 12%. Therefore, the first investment programme, which begins with the construction of the surface-water reservoir, is chosen as the least-cost alternative.

15.5.3 Costs, benefits and IERR Ideally, incremental water-use benefits should be estimated in terms of consumer willingness-to-pay (i.e. area under the demand curve – see Section 3.3.2). However, since no demand curve is available for this simple example, incremental benefits are estimated in terms of incremental revenues from users. Thus, these benefits are only a minimum measure, because consumer surplus is ignored. Further, there may be other social and environmental

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Table 15.18 Comparison of water-system expansion alternatives Present value of total costs (103L) Discount rate (%)

Alternative 1

Alternative 2

Difference

0 5 10 20 30

8721 4971 3134 1639 1129

9134 5267 3321 1649 1018

413 296 187 10 −111

Equalizing discount rate = 20.5% and opportunity cost of capital = 10% to 12%.

externalities that are difficult to value economically and are therefore excluded from this cost–benefit calculation (see Section 3.3.5). The incremental revenue (benefit) stream is calculated using the incremental water demand met (see Table 15.16). The incremental consumption benefits begin in year 2 (i.e. after two years of initial investment). The incremental water used by households (in m3) is multiplied by the average household tariff of L0.32/m3 to obtain the corresponding benefits (in domestic prices). This domestic-priced benefit is converted to border prices using the consumption conversion factor of 0.8 (see Section 3.8). Similarly, the government and industrial water-use benefits (in domestic prices) are calculated after multiplying the physical water consumption by the average government and industrial user tariff of L0.28/m3. These benefits are converted to border prices using the standard conversion factor of 0.85 (since there is no specific conversion factor for government and industry). The household, government and industrial benefits are added to yield total border-priced project benefits. The internal economic rate of return (IERR) for the project is the value which equalizes the present discounted value of the economic cost and benefit streams. In this example, this value falls between 13% and 14%. Since the opportunity cost of capital (OCC) lies in the range 10 to 12% (as indicated earlier), we see that IERR > OCC. This implies that the net present value of benefits (NPV) is positive, which provides the green light to go ahead with this investment plan (see Section 3.2.1).

15.5.4 Average incremental cost of supply and pricing policy The LRMC of water is important for efficient resource allocation in the sector (see Section 14.3). Since the investments are lumpy, the average incremental cost (AIC) may be used to estimate the LRMC. Thus, we may write: LRMC = AIC = PVC(OCC) / PVD(OCC), where PVC(OCC) = present value of costs discounted at OCC and PVD(OCC) = present value of incremental demand discounted at OCC.


543

The values of AIC range from L0.210 to L0.222/m3 of water in border prices, for discount rates of 10 to 12%. As shown in Chapter 3, dividing this AIC value by the standard conversion factor (SCF = 0.85), for governmental and industrial consumers, yields the benchmark LRMC range of AICGI = L0.248 to 0.261/m3 (in domestic prices), which may be compared with the existing average tariff level. Similarly, using the consumption conversion factor (CCF = 0.8) for household consumers, their LRMC (in domestic prices) is given by AICH = L0.263 to L0.278/m3. The prevailing average tariff levels for government/industrial and household consumers are pGI = L0.28 and pH = 0.32/m3of water, respectively, both of which are slightly higher than the corresponding benchmark values AICH and AICGI, calculated above. Economic efficiency and financial viability are among the major objectives of resource pricing policy (see Section 14.2.1). The foregoing calculations indicate that existing water prices are close to levels that will meet the economic efficiency objective. Financial viability will also be ensured, because actual tariff levels are a little greater than the AIC, so that incremental revenues exceed investment costs over the time horizon considered. If financial, sociopolitical and other constraints permit it, we might be justified in urging a small decrease in overall tariff levels, based solely on economic efficiency considerations. However, detailed recommendations on both the level and structure of tariffs ought to be made only after a thorough pricing study (see Chapter 14).

16 Local applications – hazards, disasters and urban growth1

In this chapter, we use the sustainomics framework to analyse more localized events like hazards and disasters, as well as to assess the sustainability of growth in densely populated urban areas. Section 16.1 describes how the harmful impacts of hazards on both socioeconomic and ecological systems are often exacerbated by heightened vulnerability and prior damage inflicted by unsustainable human activities. A practical framework is presented for mainstreaming sustainable hazard reduction and management (SHARM) into national development – including the stages of relief, rehabilitation and reduction (planning, preparedness and prevention). Two-way linkages between hazards and sustainable development are analysed. In Section 16.2, the SHARM approach is used to assess the impacts of the biggest single disaster in modern history – the 2004 Asian Tsunami, which resulted in over 250 000 deaths in five countries (India, Indonesia, Maldives, Sri Lanka and Thailand). Effects on the macroeconomy, vulnerable sectors, employment and livelihoods, poverty, women and children and the environment are analysed, and appropriate policy responses are identified. A comparison of the impacts of the 2004 Asian Tsunami on Sri Lanka, and of Hurricane Katrina on New Orleans in 2005, raises important questions about the role of social capital in coping with disasters. Section 16.3 describes generic issues concerning the sustainability of long-term growth in Asian cities, arising mainly from growth and pollution affecting air, water and land. Policy options to address these problems are discussed – especially in the rapidly expanding mega-cities. In Section 16.4, we study the vulnerability of urban development to environmental damage and hazards (like floods, landslides and earthquakes) and we present a case study of Rio de Janeiro. Finally, Section 16.5 provides two examples of how urban development is becoming more sustainable in developed nations – in Canada and the European Union.

16.1 Sustainable hazard reduction and disaster management (SHARM) This section describes a framework, based on sustainomics principles, to explore the links between hazards and sustainable development. The approach helps disaster experts, 1

The valuable contribution of C. Clarke to this chapter is gratefully acknowledged. Some parts of the chapter are based on material adapted from MIND (2005), Munasinghe, (1997) and Munasinghe and Clarke (1995).

544

16 Local applications hazard–disaster domain

hazards (natural, human)

545 sustainable development domain

mitigation (prepare, plan, prevent)

human activities and

vulnerability (resilience, coping capacity)

adaptation (prepare, plan, prevent)

development paths

(relief & recovery) rehabilitation natural and human systems

disasters damage (economic, social, environmental)

Figure 16.1. Circular relationship between the hazard–disaster and sustainable development domains and the role (SHARM).

development specialists and decision makers to identify measures to reduce hazard vulnerability and potential losses – by making development more sustainable (MDMS).

16.1.1 Hazards, vulnerability and disasters Since the dawn of civilization, human society, the natural environment, hazards and disasters have been closely interlinked. Both hazards and the increasing environmental degradation continue to threaten development. Humankind’s relationship with nature has gone through several stages, starting with symbiosis with nature in primitive times, through a period of increasing mastery over nature since the industrial age, when vulnerability to natural hazards was reduced. However, the rapid material-intensive growth patterns of the twentieth century have increased some hazard risks and made many groups (especially the poor) more vulnerable to disasters. Hazards are extreme events (both natural and anthropogenic) that threaten sustainable development (see Figure 16.1 and Box 16.1). When hazards strike vulnerable populations (especially the poor and disadvantaged), the consequences are often disastrous. The lefthand side of Figure 16.1 (the hazard–disaster domain) shows that hazards are potentially risky events that result in disasters when vulnerability is high. Once the disaster has struck, there will be significant damage to human and natural systems in the sustainable development domain, and rehabilitation efforts are needed to recover. The harm to human and natural systems will further affect future development efforts. At the same time, many

546


Box 16.1 Hazards, disasters, vulnerability and SHARM – definitions Hazard An extreme event that can cause significant potential damage or loss. Natural hazards are linked to nature (e.g. earthquakes, floods, storms, tsunamis, etc.). Human-induced disasters are usually of industrial origin (e.g. oil spill, chemical or nuclear accident, etc.). Hazard risk rises when either or both the magnitude and probability of occurrence of a hazard increases.

Vulnerability The degree to which socioeconomic and ecological systems are sensitive to and unable to cope with hazards. A system will suffer greater damage or loss if it is more vulnerable, less resilient and lacks adaptive capacity.

Disaster A hazard that causes significant damage or loss to a vulnerable community or locality, resulting in deaths, property losses, environmental harm and disruption of normal functions.

SHARM A practical framework that can reduce harm by integrating hazard-reduction measures into sustainable development strategy. Specific actions seek to strengthen resilience, reduce vulnerability to hazards (ex-ante) manage disasters more effectively (ex-post) and generally make development more sustainable.

(non-disaster-related) human activities are already affecting human and natural systems. Finally, alternative human development paths could increase (or decrease) both the vulnerability to, and likelihood of, future hazards. Sustainable hazard reduction and disaster management (SHARM) seeks to reduce the harm from disasters by integrating hazard reduction and disaster-management measures into sustainable development strategy. As shown in Figure 16.1, the goal is to identify actions that will make development more sustainable by recovering faster from disasters (ex-post), reducing vulnerability to hazards (ex-ante), and wherever possible mitigating future hazards (ex-ante reduction of hazard likelihood) – through planning, preparedness and prevention. This process parallels the climate-change adaptation and mitigation response measures described in Chapter 5 (see Figure 5.1). Indeed, the SHARM approach may be extended to meet the long-term challenges of climate-related extreme events.

16 Local applications

547

Types of natural disasters ‘Natural disasters’ arise from two broad categories of physical hazards – hydrometeorological (floods, droughts and storms) and geophysical (earthquakes, volcanic eruptions and related tsunamis). They have different human and economic impacts, and distinct patterns and forms of vulnerability, due to varying frequencies of occurrence and predictability. Hydrometeorological hazards, associated with climatic variability, tend to be recurrent, thereby allowing adaptation in economic and social activity, e.g. the distinctive crops and cropping patterns in flood-or drought-prone areas of Bangladesh. Climatic and hydrological records allow formal assignment of risk in investment and production decisions, e.g. adopting decision rules for water use that reflect extreme rainfall variability, or building storm-resistant infrastructure. Costly failures of prediction include the repeated hurricane-related damage to donor-funded but inadequately protected port facilities and roads in the Caribbean island of Dominica, beginning with Hurricane David in 1979 up to Hurricane Lenny in 1999, where repair and retrofitting have absorbed a high proportion of public investment. The suffering and wider economic disruption caused by poor management of southern African hydroelectric systems affected by extremely low rainfall (Kariba in 1991–1992) or very high rainfall (Caboro Baso in 1999–2000) have highlighted the need for improved science-based decision making. The potential effects of climate change are now recognized as introducing an additional source of uncertainty into the very data that underpin risk-sensitive decisions (see Chapter 5). Geophysical hazards are mostly low-probability or seemingly random events (locationspecific annual risks of under 1 in 100 or less). Over 80% of the major volcanic eruptions in the twentieth century – from Mont Pelé in 1902, which killed almost everyone in Martinique’s capital, St Pierre, to Montserrat, ongoing since 1995 and forcing 90% of the island’s population to relocate – had no precedent in historical time. Yet, in highly exposed areas, they can cause enormous loss of life, physical damage and disruption to public infrastructure and private assets. As economies grow and mega-cities emerge, more people and expanding investments across the globe are at risk from earthquakes, as demonstrated by recent disasters in Marmara, Turkey and Kobe, Japan. The Tsunami of 2004 showed that coastal locations, which have a high share of human urban activity, are vulnerable to tsunamis unleashed by seismic and volcanic activity (see Section 16.2). The geo-extent or localization of the hazard is another purely physical determinant of relative economic vulnerability. A micro-island economy such as Montserrat (area 102 km2; pre-eruption population 10 000) can be overwhelmed by an event like the Rabaul eruption of 1994, which might be less significant in Papua New Guinea (700 islands; area 463 000 km2; population 4.2 million). Dominica (area 751 km2; population 75 000) suffered many severe short-run shocks from cyclones. The latter are frequent, but scarcely disrupt the national economy in the Philippines (7200 islands; area 298 000 km2; population 76 million). Impacts Since the late 1980s, natural hazards, such as earthquakes, volcanic eruptions, landslides, floods, tropical storms, drought, locust invasions and other natural calamities have killed

548


three million people, inflicted injury, disease, homelessness and misery on one billion others, and caused billions of dollars of material damage. In the early 1990s, annual global economic costs of disasters averaged almost US $500 billion/yr (IFRC, 1996) and doubled from 1995 to 2000 (Munich Re, 1996). All these events reconfirm a relatively clear picture of disaster impacts – the human suffering, the people affected and the financial cost continue to rise precipitously. From the 1950s to the 1990s, the reported global cost of ‘natural’ disasters increased 15-fold. In 1995, the year of the Kobe earthquake, disaster-related losses of US $178 billion were equivalent to 0.7% of global GDP. For an affected country, the costs can be beyond the domestic revenue raising and commercial borrowing capacity of government: for example, after Hurricane Mitch in 1998, in Honduras, with a GNP of $850 per capita, the government faced reconstruction costs equivalent to $1250 per capita. Recent extreme events include the 9.0 Richter scale earthquake, which unleashed the 2004 Tsunami with over 250 000 deaths, and the scale 5 Hurricane Katrina in the USA, with losses put at around US $200 billion. In October 2005, the South Asian Earthquake centred on Kashmir killed tens of thousands and made over three million homeless. Meanwhile, poor harvests and pests threaten famine in the Sahel and East Africa. A major global meeting, the 1994 United Nations World Conference on Natural Disaster Reduction, in Yokohama, Japan, highlighted hazard reduction (Clarke and Munasinghe, 1995). Recently, the follow-up 2005 UN World Conference on Disaster Reduction, in Kyoto, Japan, focused on the 2004 Asian Tsunami. The developing countries, where two-thirds of the world’s population lives, suffer the most debilitating consequences due to natural disasters – 90% of all natural disasters and 95% of total disaster-related deaths occur in the developing countries. Furthermore, the risk of loss of life per million population due to disasters is 12-fold greater in the developing world than in the USA. The per capita losses in GNP in developing countries are estimated to be 20 times greater than in industrial countries. Since the 1960s, global economic losses have increased at least five-fold. Losses in the industrial countries are also rising. For example, in the highly insured USA, insurance payouts from natural disasters during 1990–1994 were more than quadruple those accumulated for all of the 1980s, which themselves were quadruple those of the previous decade. Losses are growing largely due to increasing concentration of population and investments in vulnerable locations and to inadequate investment in measures to reduce risk (UNCRD, 1994). From an economic perspective, a disaster is a shock that results in a combination of losses in the human, social and physical capital stock and a reduction in economic activity such as income generation, investment, production, consumption and employment. The poor are likely to be worst affected, with major distributional implications. There may also be severe financial effects on the revenue and expenditure of public and private bodies. Disaster experts commonly distinguish direct impacts, including physical damage (capital stock) and losses in output such as crops destroyed and reduced fish catch, from indirect impacts, including most changes in the ‘flows’ of economic activity.


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Vulnerability to hazards is determined by a complex, dynamic set of factors, such as economic structure, stage of development, prevailing economic conditions and the policy environment. Vulnerability can change quickly in countries experiencing rapid growth or socioeconomic decline. Appropriate investments in disaster mitigation and favourable developments in the structure of the economy can reduce economic vulnerability to natural hazards. Increasing sensitivity, such as that of southern Africa, reflects a complex mix of factors, including climatic variability (encompassing both droughts and floods), as well as the HIV/AIDS pandemic and a deteriorating policy environment. Most extreme events that trigger disasters are beyond human control, although some human activities increase hazard risk. For example, unsafe practices may increase the likelihood of industrial hazards (like Bhopal or an oil spill), and environmental degradation (such as soil erosion or climate change) may worsen prospects for natural hazards. More importantly, vulnerability to hazards is often the result of human behaviour. Such actions include large-scale urbanization, population exposure to hazards, natural-resource degradation, poverty, population pressure and certain patterns of consumption, production and development. Lack of an early-warning system in South East Asia (unlike the well monitored Pacific region), coupled with exposed (and often illegal) settlements in coastal areas, worsened the impact of the 2004 Tsunami. Similarly, earthquakes occur naturally, but the amount of damage they cause is largely a function of development activities. Uncontrolled growth of cities and expansion of slums into marginal areas, poor design and building techniques and lack of enforcement of land-use regulations are some development decisions that result in significant losses when an earthquake strikes. Poverty issues Economic impacts of disasters vary by country income. The least-developed countries are the most vulnerable – suffering the greatest direct losses relative to a country’s wealth. Poor groups in these nations may become even more vulnerable as socioeconomic changes force them to seek livelihoods in more hazard-prone places. However, economic losses may appear to be low, because a higher proportion of direct and indirect losses are less likely to be recorded, due to poor data. Middle-income economies are more integrated – sectorally and geographically. Hence, an impact on one area generates negative impacts on the entire economy-wide system. The government of a middle-income country is likely to meet a larger share of the costs of relief and rehabilitation, as more international assistance flow toward least-developed countries. Although financial costs of capital losses are massive in developed countries, the economic impacts of disasters are proportionately less because of better mitigation and preparedness, and greater access to financial and insurance resources. More private-sector assets are likely to be well insured against disaster, and the loss shared with both local and global insurers and reinsurers. Environmental vulnerability and poverty are mutually reinforcing: 80%, 60% and 50% of the poor in Latin America, Asia and Africa, respectively, live on marginal lands that are unproductive and highly vulnerable to environmental degradation and hazards. Developing

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countries, which must place high priority on food production and industrial activity, have fewer resources left to reduce hazard risk. Even in industrial countries, rising economic losses suggest that mitigation efforts are not keeping pace with the factors that are increasing vulnerability. Many developing countries are also experiencing rapid population growth, with increasing concentration of population and investments in vulnerable locations. These trends increase pressures on natural resources and the environment and raise the consequent risks associated with human activity. In rural areas, rangelands are heavily overgrazed and forestlands are severely degraded by overexploitation and neglect. Acute shortages of firewood have accelerated deforestation, which, together with destruction of the vegetative cover on natural pastures, has increased the threat of floods and the deterioration and desertification of previously fertile land. Rapid urbanization, and the growing scale of urban-industrial activity, is exacerbating environmental stresses in developing-country cities and increasing the vulnerability of urban dwellers to hazards – see Section 16.3 (Kreimer and Munasinghe, 1991). Accelerated changes in demographic and economic trends have disturbed the balance between ecosystems – see Chapter 4 (MA, 2005a). There is growing evidence of causal links between environmental degradation and vulnerability to hazards. Harming the environment (e.g. deforestation) can also worsen impacts of natural hazards. There is a rising correlation between the frequency and severity of extreme events and growing local and global environmental degradation – see Chapter 5 (IPCC, 2001b, 2007b). Environmental degradation intensifies disasters, thereby increasing the risk from secondary disasters: storms are followed by floods and landslides, floods by drought, and drought by pest epidemics and famines. Ecological harm due to extreme weather events has escalated, increasing faster than population growth. As greater vulnerability is linked with poverty, sustainable development oriented toward poverty alleviation will diminish the effect of hazards. Difference in losses between developing and industrial nations support this view. Nevertheless, although evidence indicates that development helps to diminish the effects of hazards (at least in the aggregate), patterns of unsustainable development – such as greater use of resources, urbanization and use of environmentally harmful technologies – have increased vulnerability. Thus, more emphasis is needed on SHARM as a key element of national sustainable development strategy.

16.1.2 Framework for mainstreaming SHARM Hazards and sustainable development As indicated above, both natural and anthropogenic disasters destroy human effort and investments, thereby placing new demands on society for reconstruction and rehabilitation. Extreme events can have profound, negative impacts on long-term development, causing distress and increasing dependency. For many years, the response to hazards and environmental threats was reactive and characterized by increased defensive activities. More


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recently, our attitude toward such risks has evolved to include the more proactive design of projects and policies, that seek to anticipate hazards and limit damage. This approach also makes development more sustainable. The basic SHARM framework has three key phases – reduction, relief and recovery (the three Rs). First, reduction focuses on ex-ante planning, prevention and preparedness (the three Ps), which lower the probability and severity of a hazard taking place and limit disaster damage by reducing vulnerability. Second, relief efforts seek to alleviate human suffering immediately the disaster has occurred. It is the short-term component of disaster management programmes, and usually lasts some days or weeks. Third, recovery refers to the shortto medium-term response of disaster management programmes, involving rehabilitation of human lives and reconstruction of damaged buildings and infrastructure, which could last a few months or years. Section 16.2 assesses the 2004 Asian Tsunami relief and (ongoing) recovery activities exante, and provides suggestions to improve future reduction and prevention strategy ex-post, based on lessons learned. Analytical framework National decision makers pay more attention to conventional development strategies that seek to achieve objectives such as economic growth, poverty alleviation, food security, human health and employment. Figure 16.2 shows that sustainable development (SD) is considered a special (and rather obscure) aspect of conventional development. In turn, the environment is one component of sustainable development, and finally natural hazards are themselves seen as a minor element of the environment. The double arrow in the figure shows the two-way links between hazards and sustainable development. It is an essential step, in the practical implementation of SHARM within a country, to show the explicit linkages between hazard risks and conventional development activities, to identify priority issues and to determine appropriate policy remedies and responses in the development domain.

environment

– cross-cutting issues (poverty, equity, etc.)

SD social, economic, environmental

development – sectors (agriculture, energy, industry, transport, health, etc.) – systems (socioeconomic, ecological, etc.)

hazard and disaster risk

Figure 16.2. Hazards–sustainable development nexus: decision makers see hazards as a minor element of national development strategy.

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Sustainable hazard-reduction and disaster-management measures ultimately must be implemented by nations, and will receive more favourable attention from both national decisions makers and the international development community if we can show their relevance for sustainable development. Thus, we start from the basic premise that the most effective way of protecting humans from hazards is to mainstream appropriate measures and policies into development activities. More specifically, SHARM seeks to integrate protective measures into sustainable development strategy at the national and local levels and implement them on a more disaggregate basis through local communities and individuals. Thus, SHARM builds on the basic elements of sustainomics, including the principle of making development more sustainable, the sustainable development triangle, transcending boundaries and full-cycle application of analytical tools (especially the Action Impact Matrix – see Section 2.4.1).

16.1.3 Two-way linkages between hazards and sustainable development Economic, social and environmental aspects As shown in Figure 16.1, hazards and sustainable development are linked in circular fashion – hazards have significant impacts on sustainable development through vulnerabilities, and, in turn, the sustainability of development paths can alter hazard risks and vulnerability. Hazards threaten prospects for sustainable development in all three dimensions. Economic, social and environmental capital is damaged by disasters, causing major losses of benefits flowing from those assets. Such losses depend on the resilience and vulnerability of socioeconomic and environmental systems. Some economic development paths can worsen vulnerability. Thus, growing interconnectedness has exacerbated hazard risks. The number of people indirectly harmed by disasters worldwide is typically 1000 times the number of people killed (Munasinghe and Clarke, 1995). For instance, losses could be propagated via capital markets, through capital flight, depreciation of domestic currency, greater indebtedness, etc. Developing economies are especially sensitive to vagaries of international capital flows, which makes them more vulnerable to disasters. Key needs for economic growth include investment, effective governance and social stability – unfortunately, disasters lead to exactly the opposite conditions. Loss of man-made and natural capital causes sudden disinvestment, postdisaster relief increases both the financial and administrative burden on government, and, finally, disasters are socially destabilizing. The social dimension of sustainable development also has a two-way link with hazards. Hazard risk and vulnerability depend on social behaviour. Conversely, disasters undermine sustainable development by eroding social capital and further increasing vulnerability. Thus, the resilience of socioeconomic systems may be increased through prevention and adaptation in anticipation of a perceived hazard risk, and more generally by making development more sustainable. The critical role of social capital in coping with disasters is explored in Section 16.2 (see Section 16.2.5).


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As the impacts of natural disasters fall disproportionately on the poor, the social view stresses the participation of at-risk communities in devising and implementing effective strategies to reduce vulnerability. Communities must directly identify site-specific solutions and assess the efficacy of proposed measures. The implementation of SHARM is best performed jointly by local communities, the government and industry. Better public awareness is essential. There is a need to understand people’s perception of risk, develop better channels of communication and popular consultation and to rely on local resources. Often, major changes due to urbanization have undermined the traditional support system for coping with crises. Decentralized decision making and subsidiarity are important to strengthen the implementation of SHARM, particularly given the need for rapid and localized responses to sudden catastrophes. For example, informal networks among slumdwellers in Turkish cities provided support for communities during crises (Parker, Kreimer and Munasinghe, 1995). Hazards also interact both ways with the environmental dimension of sustainable development. Hazards, risk and vulnerability depend on how development activities affect nature. In turn, disasters can harm the environment and hamper sustainable development. Environmental sustainability emphasizes preserving the resilience and dynamic ability of biophysical systems to adapt to external shocks and disasters. While most hazards are beyond human control, recent changes in demographic and economic trends are harming ecosystems (see Chapter 4) and increasing vulnerability to hazards. Vulnerability and poverty are mutually reinforcing. Developing countries face the most severe impacts of natural disasters. The analysis of vulnerability must include poverty, sociopolitical marginalization, lack of social safety nets and other social, political and economic indicators that cause people to act in ways which exposes them to higher risk. Often, proximity to extreme events combines with low socioeconomic status to yield deadly results. By the year 2025, 80% of the world’s population will reside in developing countries, and up to 60% of these people are highly vulnerable to extreme events (Munasinghe and Clarke, 1995). Some policy implications Economies need to incorporate disaster risk into decisions on investments (e.g. infrastructure and house construction to withstand extreme events) and share risks and costs through insurance. To formulate effective policies, externalities have to be included in cost–benefit analysis. When valuation is difficult, multicriteria analysis will reduce risk and costs. Widespread dissemination of accurate and vital information to people at risk is essential. Improved warning and mitigation have greatly reduced lives lost in technologically advanced nations. This underscores the need for developing countries to increase their own capabilities in this area. Yet, any measures are effective only when associated with appropriate regulatory structures. For developing countries, key features of broad-scope insurance programmes should include providing all natural-hazard insurance, government reinsurance to ensure stability of insurance markets and subsidized or low-cost insurance to the poor. Thus, insurance can

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be used to promote mitigative actions and limit vulnerability. Other market-based control mechanisms (pricing and taxation) may be used to reinforce such behaviour. Improved institutional arrangements, such as better urban management, are also critical. The focus must be on providing more comprehensive environmental protection within basic services. National capacity to respond to and face such unpredictable events depends on the ability to measure, appraise and evaluate possible losses. While cost–benefit analysis is useful, issues such as moral hazard problems, role of expectations and undervaluation of benefits (due to uncertainty, inadequate data or lack of accounting framework), must be recognized. When the risk is of a more global/widespread nature, and mitigation costs are large, fewer incentives exist for an individual country, especially a poor one. Cooperative efforts between countries will realize greater benefits. Finally, a comprehensive approach based on SHARM involves several elements: reduction, relief and recovery. Usually, the ex-post focus is on relief and recovery, but the greatest potential for improvement is through hazard reduction, involving planning, preparedness and prevention. Even in the recovery phase, good mitigation principles need to be exercised instead of mere rebuilding. For example, the World Bank (2004) estimated that US $3.15 billion spent on flood control in China over the final four decades of the twentieth century prevented losses of US $12 billion. Communities at risk must participate in devising and implementing effective strategies to reduce vulnerability, identifying site-specific solutions and assessing the efficacy of proposed measures. Implementation of SHARM is best performed jointly by local communities, the government and industry. Thus, there is a need to identify and understand people’s perception of risk, develop better channels of communication and popular consultation and rely on local resources and traditional support systems. Lastly, lessons learned from one phase of SHARM may be extended and applied to other phases, different countries and future hazards. 16.2 The 2004 Asian Tsunami – a preliminary assessment This case study uses the SHARM framework to review and assess the consequences of the Asian Tsunami of 2004 for five affected countries (India, Indonesia, Maldives, Sri Lanka and Thailand), in order to identify lessons learned and reduce the potential impacts of future hazards (MIND, 2005). It seeks to better understand the impacts of the 2004 Tsunami, promote sustainable development that is more resilient to the impacts of disasters and guide future decisions about ex-ante policies for hazard reduction through better prevention and management. More generally, we explore practical links between hazards and sustainable development based on recent experience, and attempt to enhance the dialogue between disaster experts, development specialists and decision makers, on reducing potential losses and long-term vulnerability of sustainable development. A more systematic method of mainstreaming SHARM measures into national sustainable development strategy would have been to use the Action Impact Matrix (AIM) – see Section 2.4.1. Furthermore, post-Tsunami recovery activities should be subjected to full sustainable development assessment (SDA) – Chapters 3 and 4. However, such a detailed analysis was


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Table 16.1 Tsunami impacts: economic, social and environmental Social

Economic

Environmental

GDP Rise in Loss growth Loss of Number Pop. of deaths displaced poverty (US $106) employment (before (’000) [% of GDP] (’000) [after]) (% pop.) (’000) Sri Lanka 35 000 (0.2) Indonesia 16 400 (0.07) Thailand 8000 (0.01) India 16 000 (0.001) Maldives

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